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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...

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....

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

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...

The purpose of this research is to use the visual inspection technique for the automatic tool wear measurement of different coated drills. The tool wear images with the different coated drilling are captured using a machine vision system incorporating with an effective vertex detection algorithm based...

In this paper we present a novel dense matching algorithm that relies on sparse stereo data in order to build a dense disparity map. The algorithm uses a recursive updating scheme to estimate the dense stereo data using various interpolation techniques. The major problem of classical template matching...

Correct classification of various kinds of scenes in sport videos is essential for higher-level content analysis such as event detection. The paper presents a novel technique for the classification of the typical scenes of baseball videos. The spatial color features are employed to detect pitch scene...

SIGNATURE RECOGNITION USING CONJUGATE GRADIENT NEURAL NETWORKS Transforming the input before training yields much lower error, but is more sensitive. Most importantly, we have presented system can vary in security depending on the situation. Uses for such a system range from securing a credit card transaction...

The portfolio optimization model, initially proposed by Markowitz in 1952 and known as mean-variance model (MV model), is applied to find the optimized allocation among assets to get higher investment return and lower investment risk. However, the MV model did not consider some practical limitations...

In this paper we introduce a practicable system by combining a vision processing algorithm and a fuzzy controller to obtain an efficient active tracker. Target tracking performance is heavily dependent on a good blend of vision algorithm and control. Because of performance and computational complexity,...

Most decision-making and problem-solving tasks are too complex to be understood quantitatively. People perform such tasks using knowledge that is imprecise rather than precise. This study presents consistent fuzzy linguistic preference relations rather than fuzzy analytic hierarchy process (FAHP) to...

Based on the fuzzy set theory, this study introduces three novel three-phase fuzzy feeder models for fast distribution system calculations. These fuzzy models are formulated using three lumped individual phase loads to represent single-phase, three-phase unbalanced, and nonuniformly distributed loads...

Once the input values are given, the active rules in a fuzzy inference execution have been determined. Based on the observation, our approach is to identify the active rules before fuzzy inference execution. To achieve this goal, our architecture provides the following two mechanisms: (1) a mechanism...

We present Pavelka-style fuzzy logic for reasoning about attribute implications, i.e. formulas $A\Rightarrow B$. Fuzzy attribute implications allow for two different interpretations, namely, in data tables with graded (fuzzy) attributes and in data tables over domains with similarity relations. The axioms...

In this paper, a comparison study for the non-stationary power signal prediction by using several neural models is presented. A reliable and accurate neural forecasting model is trying to be found and concluded. This study is expected to provide some suggestions and could be treated as a reference for...

In the fast-changing business environment, supply chains are affected by the production and inventory strategies, which influence the amount of information needed by the chains. The firms must therefore determine the best supply chain inventory strategies for their products. The lack of precise market...

Fuzzy controllers in general are designed using the experts’ knowledge or human experience in order to decide the settings of a number of system factors. However, the relations between the factors and system performance are not easy to be determined. Usually, more than one system performance characteristic...

A fuzzy logic controlled protocol that enables each station to tune its contention window based on the on-line channel sensing results is proposed for the wireless local area networks. Extensive simulations are provided to compare the performance of the proposed protocol with that of the distributed...

This work proposes a two-stage immune algorithm that embeds the compromise programming to perform multi-objective optimal capacitor placement. A new problem formulation model that involves fuzzy sets to reflect the imprecise nature of objectives and incorporates multiple planning requirements is presented....

The forum system is useful for knowledge sharing and help-seeking. However, the existed forums are having the same problem such like nobody to answer the given questions. In order to attack the problem, this study proposes a human-expert oriented forum architecture to perform efficient knowledge sharing....

In this paper, a progressive road analyzes using fuzzy technique is proposed. In this system, only the low cost GPS receivers are used. The road attribute and map are constructed only using the received data.

Modern axiomatic uncertainty theories (fuzzy logic, probability theory and others) provide a calculus for manipulating with probabilities, membership functions, and degrees of belief when the initial values such as probabilities of elementary events are already given. These theories do not include a...

By the grey-based Taguchi methods, this study attempts to analyze the process parameters pertinent to the multiple performance characteristics of linear motion guides and obtain the multiple performance characteristics of the noise level, push force value and horizontal combination precision of the linear...

An image-based fire detection method using neural networks is proposed in this paper. First, flame color features, based on the HSI color model, are trained by a backpropagation neural network for flame recognition. Then, based on the learned flame color features, regions with fire-like colors are roughly...

This paper proposes an approach to deal with the problem of producing a set of cross-level fuzzy certain and possible rules from examples with hierarchical and quantitative attributes. The proposed approach combines the rough-set theory and the fuzzy-set theory to learn. Some pruning heuristics are adopted...

A dynamic optical reconstructed system for digital hologram is developed using two commercially available twisted-nematic-liquid- crystal spatial light modulators (TNLC-SLMs), which are operating in the amplitude- and phase-mostly modulation modes, respectively. The complex modulated properties of this...

In this paper we have proposed the GROW-Net, a novel hybrid optical wireless access network architecture. GROW-Net is designed to provide cost-effective broadband access connections in a highly populated and dense metropolitan area and consists of an optical grid network that provides a broadband backhauling,...

The purpose of this study is to make a basic Foreign Exchange Market Model. It is important to make a simple basic model at first to understand the complex emergence of exchange rate which is caused by various factors. The model is a multiagent-based model, consisting of dealer and speculator. Both agents’...

Markov Chain Model provides a concise mathematical model to describe the online English auction process, converting the complicated interaction between the bidders and auctioneer into a tractable mathematical problem, which is a milestone for researches involved in this area. However, the assumptions...

The mean-variance framework for portfolio selection should be revised when investor’s concern is the downside risk. This is especially true when the asset returns are not normal. In this paper, we incorporate value-at-risk (VaR) in portfolio selection and the mean-VaR framework is proposed. Due to the...

One purpose of this paper is to propose hybrid neural network models for bankruptcy prediction. The proposed hybrid neural network models are, respecitvely, a MDA model integrated with financial ratios, a MDA model integrated with financial ratios and intellectual capital ratios, a MDA-assisted neural...

Music expresses emotion. However, analyzing the emotion in music by computer is a difficult task. Some work can be found in the literature, but the results are not satisfactory. In this paper, an emotion detection and classification system for pop music is presented. The system extracts feature values...

Objects in the world exhibit complex interactions.When captured in a video sequence, some interactions manifest themselves as occlusions. A visual tracking system must be able to track objects which are partially or even fully occluded. Occlusion is a difficult problem in target tracking, especially...

This paper presents state-of-the-art silicon-based bandstop filters for the realization of microwave system-on-a-chip (SOC) communication systems. The characteristics of the bandstop filters are designed by the adjustment of the geometric dimensions of the filters in order to meet different system requirements....

We are developing an artificial stock market model with investor agents in order to analyze characteristics of a market price. In this paper, we analyze the effects of agent’s reaction rate to technical indicators in a financial market. Intensive experiments have suggested that trend follow investor...

A link in production network is usually a creditor-debtor relationship. If a firm goes into financial insolvency state or bankruptcy, then firms on its upstream can have secondary effect from the bankruptcy. By using the recent 10 years data of bankruptcy in japan, we show that these causes of ``link...

The purpose of this paper is to study vendor selection problem with multi-vendor and multi-item in iron & steel industry. Firstly, the native fuzziness, derived from some uncertainty information, of some parameters in decision-making objectives is analyzed. After that, a fuzzy multiobjective programming...

This paper adopts the grey prediction methods, to investigate the return and volatility of major index futures among American and Eurasian markets. The grey relational theory and GM(1,N) model are further used to observe the volatility spillover effect and find the main influence factor in the volatility...

Some approaches such as path indexing, labeling, and numbering scheme have been proposed in order to facilitate query of XML data. The indexes derived by these approaches must be rebuilt if XML data is updated. The method LSDX (Labeling Scheme for Dynamic XML data) can dynamically add new labels without...