Proceedings of the 9th Joint International Conference on Information Sciences (JCIS-06)
An Empirical Investigation of Internet Banking Adoption from Bank Personnel Perspective
Wen-Hsiung Wu, Yi-Ming Tai, Mei-Se Chien, Len-Kuo Hu
About the issue of Internet banking adoption, based on technology acceptance model (TAM), past researches mainly focused on the customers, but seldom researches looked at the Internet banking adoption from banks and their personnel. The bank personnel have financial professionals and are crucial users...
Law and University Efficiency: The Amendment of the University Law in Taiwan
Rong-Ruey Duh, Jenn-Shyong Kuo
This paper examines the effect of the amendment of an education-related law on university efficiency using the 1994 University Law amendment in Taiwan as a case study. The results indicate that prior to the 1994 amendment; private universities operate in a more efficient manner than public universities....
The Credit Risk Pricing with Particle Filter Approach
Her-Jiun Sheu, Chih-Liang Liu
Traditional evaluation of firm’s market value in credit risk analysis could be contaminated by market noises. The purpose of this article is to price the credit risk in the distance to default with particle filter approach. Compared to the traditional methods, the estimate of the distance to default...
General Election Hatena: The First Political Prediction Market in Japan
Last year, a Tokyo-based internet venture firm, Hatena Co., ran a political prediction market that was designed to predict the result of the General Election of the Lower House of the Diet, held on September 11, 2005. The market showed reasonable predictive ability that was comparable with the predictions...
On Evolution of Bank Runs
Bank runs are usually happened as such that depositors panic and following the consequence of interaction between depositors withdraw their deposits. It is an issue of debt obligation between bank and depositors and an issue of bank capitals distribution among depositors. We consider the role of information...
A Pattern-based Model Transformation Approach to Enhance Design Quality
Yong-Yi Fanjiang, Jong Yih Kuo
Application of fuzzy linear programming to transportation planning decision problems with multiple fuzzy goals
This work develops a fuzzy linear programming (FLP) method for solving the transportation planning decision (TPD) problems with fuzzy goals, available supply and forecast demand. The proposed method attempts to minimize the total production and transportation costs and the total delivery time with reference...
Artificial Neural Networks in Insurance Loss Reserving
In this paper we analyse insurance data using Artificial Neural Networks (ANN). In particular, we use ANN for the problem of Loss Reserving. Loss reserving is the practice of estimating the future payments for the claims which have occurred on an insurance portfolio. A difficulty in forecasting future...
Stylized Facts in Internal Return Rates of Trend Speculators on Stock Indices
Transaction Cost Transform of Trading Volume Series in a Closed Auction Type Stock Market Model
Popularity-Based Summarization of Chinese Text: Implicit Weight-Based Features for Newspaper Articles
An efficient real-time system for active video conferencing
Leila Sabeti, Q. M. Jonathan Wu, Jason Z. Zhang
This paper describes a new approach for implementation of an efficient real-time system proper for using in active video conferencing sessions. A camera tracks presenter’s head and its movements and orientations in an unconstrained environment automatically by its pan and tilt actions. Head or face is...
A Fuzzy Scheduling System for Dedicated Machine Constraint
Arthur M.D. Shr, Alan Liu, Yen-Ru Cheng
In this paper, we propose the Fuzzy Scheduling System (FSS) to deal with the dedicated machine constraint. The constraint of having a dedicated machine for photolithography process is the new issue introduced in photolithography machinery due to natural bias. If we randomly schedule the wafer lots to...
1/f Fractal Signals Denoising with Dual-Tree Complex Wavelet Transform
Xueyan Li, Shuxu Guo, Ye Li, Jingwei Fu, Shuai Jiang
In the paper, an algorithm based on Dual-Tree Complex Wavelet Transform is proposed for process denoising. Use the variance of the wavelet coefficients at different scales to estimate the parameters of process. Adopting Maximum a Posteriori estimator estimates the wavelet coefficients of process. The...
Volatility Dynamics of the Greater China Stock Markets: A Multivariate Asymmetric Approach
Kin Yip Ho
This paper examines the volatility dynamics of the greater China stock markets (Shanghai A- and B-shares, Shenzhen A- and B-shares, Taiwan, and Hong Kong) by employing a multivariate (tetravariate) framework that incorporates the features of asymmetries, persistence, and time-varying correlations, which...
Adaptive Fuzzy Modeling For A Large-Scale Nonlinear System
A data-driven Takagi-Sugeno (TS) fuzzy model is developed for modeling a real plant with the dependent inputs, the nonlinear and the time-varying input-output relation. The collinearity of inputs can be eliminated through the principal component analysis (PCA). The TS model split the operating region...
A Near-optimal Slot Assignment Algorithm for RFID Reader Networks
Chun-Fu Lin, Frank Yeong-Sung Lin, Cheng-Ta Lee
In this paper, we propose a method that reduces the cycle time of RFID reader networks by overlapping slots. A mathematical formulation of the problem is specified and an effective heuristic algorithm is developed.
A New Model of Isoseismal Area Assessment Based on Information Granule Diffusion
Ye Xue, Chongfu Huang
Utilizing the technique of information granule diffusion and fuzzy inference with max-min operation, this paper provides a new model to estimate isoseismal area by earthquake magnitude. The model does not depend on any extra condition but scanty historical earthquake recorders. The technique of information...
Is Rate of Stock Returns a Leading Indicator of Output Growth? In the Case of Four East Asian Countries
Pei-Fen Chen, Chien-Chiang Lee, Swee Yoong Wong
The link between stock returns and economic growth has been an important research topic in the financial economic literature. The purpose of this study is to employ a threshold vector autoregressive (TVAR) approach in order to investigate the non-linear relationship between stock returns and output growth...
Dynamic Handoff Ordering Adjustment for Multimedia Cellular Network
Chow-Sing Lin, Ping-Jing Huang
In multimedia cellular network, a Mobile Host (MH) requests multimedia services and may experience handoffs to several cells. When the target cell cannot provide adequate bandwidth for a service, instead of directly dropping a request, the MH is put into the handoff queue and hopefully the request bandwidth...
A New Method for Ranking Generalized Fuzzy Numbers for Handling Fuzzy Risk Analysis Problems
Shyi-Ming Chen, Jim-Ho Chen
In this paper, we present a new method for ranking generalized fuzzy numbers for dealing with fuzzy risk analysis problems. The proposed method considers the defuzzified values, the heights and the spreads of generalized fuzzy numbers, simultaneously, for ranking generalized fuzzy numbers. It gets better...
New Methods for Evaluating Students' Answerscripts Using Vague Values
Shyi-Ming Chen, Hui-Yu Wang
In this paper, we present two new methods for evaluating students’ answerscripts using vague values, where the evaluating marks awarded to the questions in the students’ answerscripts are represented by vague values. The vague mark awarded to each question of a student’s answerscript can be regarded...
Inversion detection in text document images
Hamid Pilevar, Ramakrishnan
OCR makes it possible for the user to edit or search the document’s contents. In this paper we describe a special water fill technique for detecting the upside down text document. Each character has a upside and downside filling capacities. A character may have two sides or one side filling capacity...
A new design of laser phase-shift range finder independent of environmental conditions and thermal drift
Shahram Mohammad Nejad, Kiazand Fasihi
This paper presents a technique to improve the performance of laser phase-shift range finders. The phase measurement is performed by using a new method to extract the phase-shift data from the peak of received and transmitted intermediate frequency signal amplitudes. The pulse width modulation is used...
Accuracy Improvement in the Nano-Displacement Measurement Based on the Doppler-Interferometry Method by Cross-talk Reduction
Saeed Olyaee, Shahram Mohammad Nejad
In this paper, accuracy improvement in the displacement measurement systems using Doppler-interferometry method is presented. The cross-talk error reduction methods are also discussed. Based on the mentioned method, a new nano-displacement measurement system is designed. In the designed system, the signal...
Nanometric Displacement Measurement System Using Three-Longitudinal-Mode He-Ne Laser
Shahram Mohammad Nejad, Saeed Olyaee
In this paper, design and simulation of a nanometric displacement measurement system is discussed. The combination of the Doppler effect and interferometry method is being used. A stabilized three-longitudinal-mode He-Ne laser with 632.8nm wavelength and 35cm cavity length is used. Its primary and secondary...
Feasibility Assessment of Support Vector Regression Models with Immune Algorithms in Predicting Fatigue Life of Composites
Ping-Feng Pai, Wei-Chiang Hong, Feng-Min Lai, Jia-Hroung Wu, Shun-Lin Yang
Predicting fatigue life of composite materials is essential to increase reliability of manufacturing systems. The predicting techniques for fatigue life of composite materials are not widely investigated. The support vector regression (SVR) is an emerging forecasting technique and has been applied in...
A class of nonlinear stochastic volatility models
Jun Yu, Zhenlin Yang
This paper proposes a class of nonlinear stochastic volatility (SV) models based on the Box-Cox transformation. The proposed class encompasses many parametric SV models that have appeared in the literature, including the well known lognormal SV model, and has an advantage in the ease with which different...
A QoS Improvement for Mobile Network in Large Vehicles
Chia-Hui Wang, Te-Chih Wang
In large vehicles such as a train, passengers can access Internet through an in-vehicle mobile router to effectively reduce the cost and overhead of roaming to a new network. While we apply the idea of mobile network into large vehicles, the critical issue is how to build up seamless Internet access...
Scheduling Mechanism for WLAN Frame Aggregation with Priority Support
Yang-Sheng Lin, Jun-Yao Wang, Wen-Shyang Hwang
For the overheads of 802.11 WLAN, several frame aggregation mechanisms had been proposed to deal with this shortcoming. Since the rare consideration of QoS in these proposals, we took advantage of 802.11e queueing model to enhance the priority scheduling. This paper approaches to eliminate the decomposition...
Hybrid wavelet -SVMs for modelling derivatives valuation
Hsing-Wen Wang, Shian-Chang Huang
Due to the rapid grow up of transaction volume of derivatives in the financial market, the Black-Scholes options pricing model (BSM) is played an important role recently and widely applied in various options contract. However, this theoretical model limited by the influences of many unexpected real world...
Understanding Social Complex Systems with PlatBox Simulator
This paper presents a framework and tools for modeling and simulating societies as complex systems. Although the concept of the complex systems has been highly demanded in social sciences, there is no satisfactory scheme for modeling and simulating it. In this paper, we propose the model framework, which...
Evaluating Uncertain Income Streams under a Regime-Switching Process
Yungchih George Wang
This paper extends the dynamic programming, utility maximization model proposed by Wang (2004) to value an investment opportunity whose income streams follows a regime-switching process in incomplete markets. Specifically, the model is applied to solve for certainty equivalent of an investment opportunity...
Dynamic Asset Allocation under Stochastic Volatility - Theory and Practice
This study develops inter-temporal dynamic asset allocation with stochastic volatility (DAASV) models. The DAASV models integrate the stochastic volatility feature inherent in asset returns into the allocation procedure. By applying the DAASV, an investor can more efficiently diversify the unsystematic...
Convergence of GARCH Estimators: Theory and Empirical Evidence
Dietmar Maringer, Peter Winker
The convergence of estimators, e.g., maximum likelihood estimators, for increasing sample size is well understood in many cases. However, even when the rate of convergence of the estimator is known, practical application is hampered by the fact, that the estimator cannot always be obtained at tenable...
Assessing the Effect of Oil Price Shock Using an Energy-Economy Decision Model with Technology Characteristics
Shih-Mo Lin, Chin-Wen Yang, Chung-Huang Huang
The significant jump in world crude oil price over the past year has raised great concern over the economic impact that such a price shock may bring about on Taiwan’s economy, which has been characterized by extremely high import-oil dependence. Previous analyses have been tackling similar issue from...
The Influence of Investor Psychology on Disposition Effect
Shu Chun Hsiao, Sun Pi-Chuan
In 1980s, many empirical researches’ findings (i.e., Shiller(1984), Thaler (1985) et al. ) did not support efficient market hypothesis (EMH). Previous studies (e.g., Bernartzi and Thaler, 1995) related to behavioral model suggest that certain market anomalies are consistent with the presence of irrational...
Complexity and entropy density analysis of the Korean stock market
Jeong won Lee, Joongwoo Park, Hang-Hyun Jo, Jae-Suk Yang, Hie-Tae Moon
In this paper, we studied complexity and entropy density of stock market by modeling epsilon-machine of Korean Composition Stock Price Index (KOSPI) from year 1992 to 2003 using causal-state splitting reconstruction (CSSR) algorithm.
The Sequential Compound Option Pricing with Random Interest Rate and Application to Project Valuation
Meng-Yu Lee, Fang-Bo Yeh, An-Pin Chen
This paper proposes the pricing formula of sequential compound options (SCOs) with random interest rate and the applications call Milestone Project Valuation (MPV). Most compound options in literatures are 2-fold with constant parameters through time. The multi-fold compound options are just sequential...
Warrants Price forecasting using kernel machine and EKF-ANN: a comparative study
Hsing-Wen Wang, JIAN-HONG WANG, TSE-PING DONG, SHENG-HSUN HSU
The Black-Scholes options pricing model (BSM) is limited by the influences of many unexpected real world phenomena caused due to its six unreasonable assumptions, which often make the miss-pricing result because of the difference of market convention in practical. If we were to soundly take these phenomena...
The Indicators of M&A or Green Field Investment Behavior: the Evidence from Power Industry
Qiusheng Zhang, Guanghui Ye, Yunhua Chen
M&A and green field investment (GFI) are very important methods of company growth. Each of the investment ways could bring different outstanding achievement and development of company, so it is very important to choose the way of investment. This paper discusses the boundary of M&A and green field investment...
Long-Term Asset Management Strategy under Loss Aversion: A Quasi-Ladder Payoff Distribution Approach
Huai-i Lee, Hsinan Hsu, Len-Kuo Hu
The prospect theory implies that the inclusion of a gain-lock-in device into the floor of portfolio insurance can benefit the long-term asset management under loss aversion. We find that the relaxation of the multiple of the CPPI from a constant to a dynamic can improve the performance in the short-term....
An Improvement on Secure E-mail Protocols Providing Perfect Forward Secrecy
Iuon-Chang Lin, Yang-Bin Lin, Chung-Ming Wang
In 2005, Sun, Hsieh, and Hwang proposed two secure e-mail protocols with perfect forward secrecy. In the first protocol, the authors apply smart card and Diffie-Hellman key agreement scheme to achieve the perfect forward secrecy. However, due to it requires a smart card to store some parameters, it is...
An Interactive Intelligent Search Engine Model Research Based on User Information Preference
Dan Meng, Xu Huang
Web service is very important for both e-commerce and e-government. However, web service process based on syntax level can’t deal with some user query very effectively. In order to make user get more information on the internet, semantic web is presented and a lot of related research results have been...
Mining Objects Correlations to Improve Interactive Virtual Reality Latency
Shao-Shin Hung, Hsing-Jen Chen, Damon Shing-Min Liu
Object correlations are common semantic patterns in virtual reality systems. They can be exploited for improving the effectiveness of storage caching, prefecthing, data layout, and minimization of query-response times. Unfortunately, this information about object correlations is unavailable at the storage...
Fuzzy Distance of Trapezoidal Fuzzy Numbers
Shan Huo Chen, Chien-Chung Wang
Fuzzy distance is applied on data analysis, classification, and production positioning analysis widely. In this paper, We introduction a fuzzy distance by using graded mean integration representation of generalized fuzzy number and the span of fuzzy number, We also discuss the distance of the linguistic...
Adaptive PI Control of Piezoelectric Systems Using Takagi-Sugeno Fuzzy Logic
This paper presents the nano-positioning control of a piezoelectric platform. A Bouc-Wen model is established to describe the nonlinear hysteretic effect of piezoelectric systems. Three kinds of compensators, traditional PI controller, PI-like fuzzy logic controller (FLC) and adaptive PI-FLC controller,...
Enhancing Performance of Relational Fuzzy Neural Networks with Square BK-Products
Warren L. Davis IV, Ladislav Kohout
In this paper, we extend research done in max-min fuzzy neural networks in several important ways. We replace max and min operations use in the fuzzy operations by more general t-norms and co-norms, respectively. In addition, instead of the Łukasiewicz equivalence connective used in the network of Reyes-Garcia...
Investigate C+L Band EDFA/Raman Amplifiers by Using the Same Pump Lasers
Shien Kuei Liaw
A novel hybrid C+L band EDFA/RFA is designed to share the 1480 nm pump laser(s). The concepts are based on three-level amplification mechanism for the C band EDFA and Raman shift amplification mechanism for the L band RFA, respectively. It has the advantage to simplify the pump source design. The optimum...
High Performance Ring-Cavity Tunable Lasers
Shien Kuei Liaw
We report the investigation of ring cavity tunable laser, which is based on FBG technology. The laser linewidth, power variation and tuning range are 0.015 nm, 0.5 dB and 31.0 nm, respectively. The ring-cavity tunable laser also has 60 dB of SMSR to insure high-quality operation. With the features mentioned...
CPW Filters with Defected Ground Structures for RF and Microwave Applications
Yeong-Lin Lai, Pei-Yen Cheng
New coplanar waveguide (CPW) filters with a fork-shaped defected ground structure (DGS) are proposed for radio-frequency (RF) and microwave applications. The miniature CPW DGS filters developed are based on the silicon technology. The filters are able to provide the bandstop characteristics with high...
New All-optical Wavelength Auto-router Based on Multibranch Waveguides
Shih-Yuan Chen, Mao-Hsiung Chen, Yaw-Dong Wu, Chih-Fu Chang
A new optical device for wavelength auto-router was proposed. Such a structure is useful in the integrated-optic for optical operation and data communication. We use the finite-difference beam propagation method to investigate the phenomenon of the proposed numerical model.
Enhancement of Tera-Hertz Radiation by carrier dynamics modulation with chirped optical pulses
Performance Assessment of MC Placement for Multicast Routing in WDM Networks with Spare Light Splitting
I-Shyan Hwang, Tsung-Ching Lin, Zen-Der Shyu
This investigation examines all-optical multicast routing in wavelength-routed optical networks with sparse Multicast Capable (MC) nodes that have three phases. The first phase is the MC node placement, and the maximum path count first (MPCF) algorithm is utilized to obtain candidates for MC nodes. The...
Variable Selection Method Affects SVM-based Models in Bankruptcy Prediction
Chih-Hung Wu, Wen-Chang Fang, Yeong-Jia Goo
This paper examined bankruptcy predictive accuracy of five statistics models--discriminant analysis logistic regression, probit regression, neural networks, support vector machine (SVM), and genetic-based SVM (GA-SVM) that influenced by variable selection. Empirical results indicate that the SVM-based...
The time-series relation between monthly sales and stock prices
Yann-ching Tsai, Hsueh-Fang Chien, Shu-Hua Lee
Security Exchange Commission in Taiwan requires all public companies to file and announce their monthly sales figure by the of the following month. This requirement has established another channel for market investors to obtain additional accounting information on a more timely basis than quarterly or...
A Framework for Knowledge-based Management Model on Decision-Making
Shao-Shin Hung, Damon Shing-Min Liu
Knowledge management (KM) is suggested as a method to manage and apply knowledge for business management. In this paper, we suggest a framework based on OPF (Open Process Framework) meta model for the knowledge-based decision-making. Based on the modeling method of OPF, we can translate partial and implicit...
A novel OoS-aware Routing for ad hoc networks
Tung-Shih Su, Chih-Hung Lin, Wen-Shyong Hsieh
Most routing protocols focus on obtaining a workable route without considering network traffic condition for a mobile ad hoc network (MANET). Therefore, the quality of service (QoS) is not easily achieved by the real time or multimedia applications. To support QoS, this work proposes a QoS-aware routing...
A User-centric Intrusion Detection System by Using Ontology Approach
Shao-Shin Hung, Damon Shing-Min Liu
In the security infrastructure, intrusion detection has become an indispensable defense line in face of increasing vulnerabilities exposed in today’s computing systems and Internet. In this paper, our approach uses ontologies as a way of grasping the knowledge of a domain, expressing the intrusion detection...
A Study on Imputing Censored Observations for Exponential Distribution Based on Random Censoring
Censoring models are frequently employed in reliability analysis to reduce experimental time. There are three censoring model: type-I, type-II and random censoring. In this study, we focus on the right-random censoring model. In the previous literature, an imputation of the censored observation is considered...
String Filtering of a Large String Collection on Mobile Devices using a Neural Network
Heng Ma, Chia-Cheng Liu
String matching of a large string collection on mobile devices has been a difficult problem because of the memory space and computing speed constraints. We propose a method to efficiently determine whether a query string exists in the large string collection. The proposed method, based on a string encoder...
Novel BCD Circuits Design Using And-Or-Inverter Gate and Its Quantum-Dot Cellular Automata Implementation
JiaChun Lin, JenYin Yeh, WeiChih Tsai
Quantum-dot cellular automata (QCA) provide a novel electronics paradigm for information processing and communication. A basic quantum-dot cell consists of several quantum dots with two excess electrons. A binary coded decimal (BCD) and a decimal coded binary (DCB) circuit based on QCA logic gates: the...
Applying XCS Model to Spread Trading of Taiwan Stock Index Futures
Jung-Bin Li, Shih-Chuan Fu, An-Pin Chen
This study attempts to find the possibility of making relatively higher profit with lower risk when trading futures commodities. The system applies XCS classifiers to explore the rules of spread trading of these commodities. Our simulation holds a trading strategy that in every transaction, the proposed...
An Empirical Study for Dynamic TIPP Policy Using XCS with Knowledge Rules
Mei-Chih Chen, Ming-Chia Huang, An-Pin Chen
The purpose of this empirical study is intended to investigate XCS (Extended Classifier System) based model with knowledge rules for dynamic TIPP (Time Invariant Portfolio Protection) policy. There are two XCS-based agents in the proposed model (MA-TIPP).One agent dynamically optimizes Multiple and Tolerance...
An Information Theoretic Approach to Market Index Prediction
New Approach to Financial Time Series Forecasting - Quantum Minimization Regularizing BWGC and NGARCH Composite Model
Bao Rong Chang, Hsiu Fen Tsai
A hybrid BPNN-weighted GREY-C3LSP prediction (BWGC) is used for resolving the overshooting phenomenon significantly; however, it may lose the localization once volatility clustering occurs. Thus, we propose a compensation to deal with the time-varying variance in the residual errors, that is, incorporating...
Learning Martingale Measures From High Frequency Financial Data to Help Option Pricing
Hung-Ching (Justin) Chen, Malik Magdon-Ismail
We provide a framework for learning risk-neutral measures (Martingale measures) for pricing options from high frequency financial data. In a simple geometric Brownian motion model, a price volatility, a fixed interest rate and a no-arbitrage condition suffice to determine a unique risk-neutral measure....
Analysis of factors which contribute to inter-enterprise competition
Takumi Shimizu, Yusuke Takada, Takashi Iba
In this paper, we replicate Nelson-Winter model in order to analyze the inter-enterprise competition from the perspective of economic change. For this purpose, we build the simulation model as Multi-Agent-Based Simulation in PlatBox Simulator. By replicating the Nelson-Winter model, which clarifies the...
Does Money Matter? An Artificial Intelligence Approach
Jane Binner, Barry Jones, Graham Kendall, Jonathan Tepper, Peter Tino
This paper provides the most complete evidence to date on the importance of monetary aggregates as a policy tool in an inflation forecasting experiment. Every possible definition of ‘money’ in the USA is being considered for the full data period (1960 – 2006), using the most sophisticated non-linear...
Stock Data Mining through Fuzzy Genetic Algorithms
Longbing Cao, Chao Luo, Jiarui Ni, Dan Luo, Chengqi Zhang
Stock data mining such as financial pairs mining is useful for trading supports and market surveillance. Financial pairs mining targets mining pair relationships between financial entities such as stocks and markets. This paper introduces a fuzzy genetic algorithm framework and strategies for discovering...
Dimensionality Reduction using GA-PSO
Cheng-Hong Yang, Chung-Jui Tu, Jun-Yang Chang, Hsiou-Hsiang Liu, Po-Chang Ko
The feature selection process can be considered a problem of global combinatorial optimization in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable classification accuracy. In this paper, we propose a combination of genetic...
Uniform Delivered Pricing is Essentially Freight Absorption PricingåÁGA Theoretical Model with Simulation
Two Are Better than One?
In this paper we adopt the Markov-switching specification to establish the hybrid model with time-varying loading on each of chartist and fundamentalist techniques. The US dollar exchange rates of four Asian tiger countries’ currencies serve as the representative examples in this paper. Our empirical...
An Evolutionary Weight Encoding Scheme and Crossover Methodology in Portfolio Assets Allocation
Ping-Chen Lin, Po-Chang Ko, Hsin-Chieh Wang
Most of GA-based portfolio assets allocation uses normalization method to allocate investment asset’s weight. However, the normalization process will cause unease converging and even diverging characteristics, because it changes the gene’s relativity of address in chromosome. In this paper, we propose...
Time series data analysis using probabilistic and neural network
Artificial intelligence decision support system is always a popular topic in providing the human user with an optimized decision recommendation when operating under uncertainty in complex environments. The particular focus of our discussion is to compare different methods of artificial intelligence decision...
Stock Trend Analysis and Trading Strategy
Hongxing He, Jie Chen, Jin Huidong, Chen Shu-Heng
This paper outlines a data mining approach to analysis and prediction of the trend of stock prices. The approach consists of three steps, namely partitioning, analysis and prediction. A modification of the commonly used k-means clustering algorithm is used to partition stock price time series data. After...
Oligopolistic Interdependency in a Mixed Market
This paper uses data from Taiwan’s banking sector to investigate if state-owned banks can serve as an internal regulation mechanism to sustain market competition. In contrast to the traditional second-best literature, the evidence shows that a certain degree of market coordination exists in the industry,...
Using Fuzzy Regression and Neural Network to Predict Organizational Performance
As everyone knows, multiple regression analysis is an important approach to prediction studies. However, regression model has some limitations and constraints in the real world practices. This study applied fuzzy regression using neural network (FRNN) to predict organizational performance, and the findings...
The Development of Neural Network Models by Revised Particle Swarm Optimization
Peitsang Wu, Chin-Shiuh Shieh, Jar-Her Kao
A novel training paradigm for artificial neural networks had been developed and presented in this article. In the proposed approach, a revised version of particle swarm optimization (PSO) had been employed to find out the optimal connection weights of feed-forward artificial neural networks for given...
How does Sample Size Affect GARCH Models?
HS Raymond NG, KP LAM
GARCH model has a long history and permeates the modern financial theory. Most researchers use several thousands of financial data and maximum likelihood to estimate the coefficients of model. Statistically, more samples imply better estimation but are hard to obtain. How many samples are sufficient...
Decision Support for IC Molding Parameter Settings Using Grey Relational Analysis and Neural Network
Yu-Min Chiang, Chung-Hsien Chou, Yung-Yuan Chuang
In order to be competitive in the semiconductor manufacturing industry, quality improvement and yield enhancement have received increasing attention. The research focuses on the molding process of Integrated Circuit (IC) assembly. The defects often occurred in molding process include hole, vein, crack,...
Evolutionary Fuzzy Case-based Reasoning for Financial Performance Ranking
Sheng-Tun Li, Hei-Fong Ho, Yi-Chung Cheng
we propose a hybrid decision model for supporting the ranking financial status of corporations using case-based reasoning augmented with genetic algorithms and the fuzzy nearest neighbor method. An empirical experimentation on 746 cases was conducted that shows that the average accuracy of the ranking...
Building a Concept Hierarchy by Hierarchical Clustering with Join/Merge Decision
Huang-Cheng Kuo, Tsung-Han Tsai, Huang Jen-Peng
Concept hierarchies are important for generalization in many data mining applications. We propose a method to automatically build a concept hierarchy from a provided distance matrix. The method is a modification of traditional agglomerative hierarchical clustering algorithm. When two closest clusters...
Two-dimentional Encoding Schema and Genetic Operators
Tzung-Pei Hong, Ming-Wen Tsai, Tung-Kuan Liu
In this paper, we propose a new genetic algorithm based on the two-dimensional encoding method. Appropriate two-dimensional crossover and mutation operations are designed based on the two-dimensional representation to generate the next generations. A two-dimensional repairing mechanism is also proposed...
A quantum model of dynamic interdependent uncertainties for industrial organizations
William Lawless, Laurent Chaudron
A major failure of rational models (cognitive science, game theory) of organizations is the use of static concepts of interdependence to predict dynamic behavior. A quantum model of organizations transforms the traditional model with its dynamic interdependence of uncertainty. We consider field and laboratory...
Return Distribution under Behavioral Biases: A Numerical Simulation Study
Xiaoguang Yang, Fenghua Wen, Delong Huang, Qiujun Lan
Investors’ overconfidence and regret aversion lead to behavioral biases, such as over-reaction、under-reaction and disposition effect. By constructing a numerical simulation model, this paper shows that, return distributions under the behavioral biases have higher peaks and fatter tails, and they are...
A Knowledge Discovery Approach to Supporting Crime Prevention
Sheng-Tun Li, Fu-Ching Tsai, Shu-Ching Kuo, Yi-Chung Cheng
The main objective of this study is developing a linguistic cluster model in order to meet the public security index requirement and extract crime rule in time series. In contrast to the current studies in crime theory which mostly rely on traditional behavior science, we turned to a hybrid approach...
Does Information Technology Always Help? Theory and Evidence from Taiwan's Banking Industry
Hsieh Meng-Fen, Shirley J. Ho
Information technology (IT) has been extensively adopted in banking industries. The reasons for this massive adoption of IT are mainly twofold: for individual banks, IT can reduce banks’ operational costs (the cost advantage), and facilitate transactions among customers within the same network (the network...
Applying Grey Relation Analysis to Establish the Financial Distress Prediction Model for Electronic Companies in Taiwan
Meng-Fen Hsieh, Rong-Tsu Wang, I-Chuan Lu
Most researches have focused on the use of document feedback or factor analysis as metrics for financial distress prediction. The theoretical basis for the former is relatively weak, while the latter is severely limited by data requirements. As such, this paper will instead use grey relation analysis...
Super-fair Platforms Widely Hidden in Multinational Securities Business
Ruan Jishou, Jun He, Qi Dai
A general phenomenon puzzles all investors is that on one hand, most individual investors believe they need to construct the portfolio consisting of 15 or more stocks to prevent risk because that large investment companies frequently get high returns is due to they obey the existing investment theory...
An Application of Intellectual Capital on Financial Distress Models by Using Neural Network
Kuang-Hua Hsu, Jian-Fa Li, Hon-Jenq Fan
As the era of knowledge economy is prevalent in U.S. during 1992, knowledge economy plays an important role around the world. The value and competition of the traditional companies accounted on tangible assets. However, in the era of knowledge economy, the value and continuing operation of the companies...
Recognition of profitable customers for dental services marketing--a case of dental clinics in Taiwan
Bih-Yaw Shih, Wan-I Lee, Yi-Shun Chung, Ai-Wei Chen, Yichaio Sui
The medical care industry has been dramatically developed in the last two decades in Taiwan and it has resulted in an extremely risky position. The purpose of the research was the development of a neural network model to recognize profitable customers for dental services marketing. Data set was built...
3D model retrieval based on Grid Sphere and Dodecahedral Silhouette Descriptors
With the development of computer graphics and virtual realities, the demand for a content-based 3D model retrieval system becomes urgent. In this study, two features, grid sphere and dodecahedral silhouettes, are proposed and combined for 3D model retrieval. The experiments are conducted on a 3D model...
Apriori Data Mining on Rotationally Invariant Multiresolutional Moments for Pattern Recognition
Annupan Rodtook, Stanislav Makhanov
We propose a new feature selection procedure based on a combination of a pruning algorithm, Apriori mining techniques and fuzzy C-mean clustering. The feature selection algorithm is designed to mine on a multiresolution filter bank composed of rotationally invariant moments. The numerical experiments,...
Finding The Finger By The Boundary Vector Product
A finger finding procedure has been presented to recognize the finger number of the hand gesture. The hand gesture is extracted from the stationary background and transformed into a binary image. The hue attribute, that is, the I value in the YIQ color space is used to extract the hand gesture shape....
Object-Based Accumulated Motion Feature for the Compressed Domain Human Action Analysis
Cheng-Chang Lien, Chen-Yu Hong, Yu-Ting Fu
This paper proposed an effective and robust method to detect the rare behavior events within the compressed video directly. New motion feature called object-based accumulative motion vector (OAMV) is generated to extract a prominent motion feature and then polar histograms are used to describe the distribution...
Natural Scene Segmentation Based on Information Fusion and Homogeneity Property
Heng-Da Cheng, Manasi Datar, Wen Ju
This paper presents a novel approach to natural scene segmentation. It uses both color and texture features in cooperation to provide comprehensive knowledge about every pixel in the image. A novel scheme for the collection of training samples, based on homogeneity, is proposed. Natural scene segmentation...
An Improved Vector Quantizer Design Method: the Codebook Reorganization Algorithm
Ting-Wei Hou, Houng-Kuo Ku, Yuan-Tsung Chen
Generalized Lloyd Algorithm(GLA) is important in vector quantizer design. It runs fast, but it is sensitive to initial conditions and it may find a local optimum. We propose an improved approach based on GLA, named vector quantized codebook reorganization algorithm (VQCRA). VQCRA finds better codebooks...
Data Fusion and Multi-fault Classification Based On Support Vector Machines
Guohua Gao, Yongzhong ZHANG, Yu ZHU, Guanghuang DUAN
As a new general machine-learning tool based on structural risk minimization principle, Support Vector Machines (SVM) has the advantageous characteristic of good generalization. For this reason, the application of SVM in fault diagnosis field has becomes one growing reach focus. In this paper, data fusion...
Head-Shoulder Moving Object Contour Tracking using Shape Model
Yong-Ren Huang, Chung-Ming Kuo, Chaur-Heh Hsieh
This paper proposes a new approach for tracking the contour of moving object for head-shoulder video sequence using initial shape model. First, we can utilize manual process or some segmentation approach to obtain the initial shape model. Then, we detect the changing ratio of intensity outside the bounding...