International Journal of Computational Intelligence Systems

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1026 articles

Some Measures Relating Partitions Useful for Computational Intelligence

Ronald R. Yager
Pages: 1 - 18
SOME MEASURES RELATING PARTITIONS USEFUL FOR COMPUTATIONAL INTELLIGENCE We investigate a number of measures relating partitions. One class of measures we consider are congru- ence measures. These measures are used to calculate the similarity between two partitionings. We provide a number of examples...

Team Situation Awareness Using Web-based Fuzzy Group Decision Support Systems

Jie Lu, Guangquan Zhang, Fengjie Wu
Pages: 50 - 59
Situation awareness (SA) is an important element to support responses and decision making to crisis problems. Decision making for a complex situation often needs a team to work cooperatively to get consensus awareness for the situation. Team SA is characterized including information sharing, opinion...

Current Computational Trends in Equipment Prognostics

J. Wesley Hines, Alexander Usynin
Pages: 94 - 102
CURRENT COMPUTATIONAL TRENDS IN EQUIPMENT PROGNOSTICS The article overviews current trends in research studies related to reliability prediction and prognostics. The trends are organized into three major types of prognostic models: failure data models, stressor models, and degradation models. Methods...

Assessment of Strategic R&D Projects for Car Manufacturers Based on the Evidential Reasoning Approach

Xin-bao Liu, Mi Zhou, Jian-bo Yang, Shan-lin Yang
Pages: 24 - 49
Assessment of strategic R&D projects is in essence a multiple-attribute decision analysis (MADA) prob- lem. In such problems, qualitative information with subjective judgments of ambiguity is often provided by people together with quantitative data that may be imprecise or incomplete. A few approaches...

Intelligent Interaction for Human-Friendly Service Robot in Smart House Environment

Z. Zenn Bien, Hyong-euk Lee, Jun-hyeong Do, Yong-hwi Kim, Kwang-hyun Park, Seung-eun Yang
Pages: 77 - 93
The smart house under consideration is a service-integrated complex system to assist older persons and/or people with disabilities. The primary goal of the system is to achieve independent living by various robotic devices and systems. Such a system is treated as a human-in-the loop system in which...

From Fuzzy Clustering to a Fuzzy Rule-Based Classification Model

Enrico Zio, Piero Baraldi, Irina Crenguta Popescu
Pages: 60 - 76
The applicability in practice of a diagnostic tool is strongly related to the physical transparency of the un- derlying models, for the interpretation of the relationships between the involved variables and for direct model inspection and validation. In this work, a methodology is developed for transforming...

Word Similarity from Dictionaries: Inferring Fuzzy Measures from Fuzzy Graphs

Vicenc Torra, Yasuo Narukawa
Pages: 19 - 23
WORD SIMILARITY FROM DICTIONARIES: INFERRING FUZZY MEASURES FROM FUZZY GRAPHS The computation of similarities between words is a basic element of information retrieval systems, when retrieval is not solely based on word matching. In this work we consider a measure between words based on dictionaries....

A Comparative Study of Various Probability Density Estimation Methods for Data Analysis

Alex Assenza, Maurizio Valle, Michel Verleysen
Pages: 188 - 201
Probability density estimation (PDF) is a task of primary importance in many contexts, including Bayesian learning and novelty detection. Despite the wide variety of methods at disposal to estimate PDF, only a few of them are widely used in practice by data analysts. Among the most used methods...

Language Identification of Kannada, Hindi and English Text Words Through Visual Discriminating Features

M.c. Padma, P.a. Vijaya
Pages: 116 - 126
In a multilingual country like India, a document may contain text words in more than one language. For a multilingual environment, multi lingual Optical Character Recognition (OCR) system is needed to read the multilingual documents. So, it is necessary to identify different language regions of...

A Linguistic Multigranular Sensory Evaluation Model for Olive Oil

Luis Martinez, Macarena Espinilla, Luis G. Perez
Pages: 148 - 158
Evaluation is a process that analyzes elements in order to achieve different objectives such as quality inspection, marketing and other fields in industrial companies. This paper focuses on sensory evaluation where the evaluated items are assessed by a panel of experts according to the knowledge...

An application of effective genetic algorithms for Solving Hybrid Flow Shop Scheduling Problems

Cengiz Kahraman, Orhan Engin, Ihsan Kaya, Mustafa Kerim Yilmaz
Pages: 134 - 147
This paper addresses the Hybrid Flow Shop (HFS) scheduling problems to minimize the makespan value. In recent years, much attention is given to heuristic and search techniques. Genetic algorithms (GAs) are also known as efficient heuristic and search techniques. This paper proposes an efficient genetic...

Online Feature Selection for Classifying Emphysema in HRCT Images

M. Prasad
Pages: 127 - 133
Feature subset selection, applied as a pre- processing step to machine learning, is valuable in dimensionality reduction, eliminating irrelevant data and improving classifier performance. In the classic formulation of the feature selection problem, it is assumed that all the features are available...

Set-Valued Stochastic Lebesque Integral and Representation Theorems

Jungang Li, Shoumei Li
Pages: 177 - 187
In this paper, we shall firstly illustrate why we should introduce set-valued stochastic integrals, and then we shall discuss some properties of set-valued stochastic processes and the relation between a set-valued stochastic process and its selection set. After recalling the Aumann type definition...

Artificial Immune Networks: Models and Applications

Xian Shen, X.z. Gao, Roufang Bie
Pages: 168 - 176
Artificial Immune Systems (AIS), which is inspired by the nature immune system, has been applied for solving complex computational problems in classification, pattern rec- ognition, and optimization. In this paper, the theory of the natural immune system is first briefly introduced. Next, we...

New Vector Ordering in the RedGreenBlue Colour Model with Application to Morphological Image Magnification

Valérie De Witte, Stefan Schulte, Etienne E. Kerre
Pages: 103 - 115
In this paper we present a new vector ordering ≤RGB for colours modelled in the RedGreenBlue colour model. The RedGreenBlue colour model becomes with this new ordering and associated minimum and maximum operators a complete lattice. We also have defined a complement co for colours in the RedGreenBlue...

Clinical Decision Support Systems: a Review of Knowledge Representation and Inference under Uncertainties

Guilan Kong, Dong-ling Xu, Jian-bo Yang
Pages: 159 - 167
This paper provides a literature review in clinical decision support systems (CDSSs) with a focus on the way knowledge bases are constructed, and how inference mechanisms and group decision making methods are used in CDSSs. Particular attention is paid to the uncertainty handling capability of...

A Knowledge Based Recommender System with Multigranular Linguistic Information

Luis Martinez, Manuel J. Barranco, Luis G. Perez, Macarena Espinilla
Pages: 225 - 236
Recommender systems are applications that have emerged in the e-commerce area in order to assist users in their searches in electronic shops. These shops usually offer a wide range of items that cover the necessities of a great variety of users. Nevertheless, searching in such a wide range of items...


Tianrui Li, Yang Xu
Pages: 0 - 0

A Linguistic-Valued Weighted Aggregation Operator to Multiple Attribute Group Decision Making with Quantative and Qualitative Information

Xiaobing Li, Da Ruan, Jun Liu, Yang Xu
Pages: 274 - 284
In selecting an optional alternative in an environment of multiple attribute group decision making, different attributes of the alternative are often considered as with quantitative and qualitative information. Consequently, decision making problems may include preference information in different formats....

Attack Pattern Analysis Framework for a Multiagent Intrusion Detection System

Grzegorz Kolaczek, Krzysztof Juszczyszyn
Pages: 215 - 224
The paper proposes the use of attack pattern ontology and formal framework for network traffic anomalies detection within a distributed multi-agent Intrusion Detection System architecture. Our framework assumes ontology-based attack definition and distributed processing scheme with exchange of communicates...

Using Parametric Functions to Solve Systems of Linear Fuzzy Equations with a Symmetric Matrix

Annelies Vroman, Glad Deschrijver, Etienne E. Kerre
Pages: 248 - 261
A method to solve linear fuzzy equations with a symmetric matrix is proposed. Ignoring the symmetry leads to an overestimation of the solution. Our method to find the solution of a system of linear fuzzy equations takes the symmetry of the matrix into account and is based on parametric functions. It...

Building an Associative Classifier Based on Fuzzy Association Rules

Zuoliang Chen, Guoqing Chen
Pages: 262 - 272
Classification based on association rules is considered to be effective and advantageous in many cases. However, there is a so-called "sharp boundary" problem in association rules mining with quantitative attribute domains. This paper aims at proposing an associative classification approach, namely Classification...

Situation Assessment in Disaster Management

Juan Carlos Augusto, Hui Wang, Jun Liu
Pages: 237 - 247
We present a framework for decision-making in relation to disaster management with a focus on situation assessment during disaster management monitoring. The use of causality reasoning based on the temporal evolution of a scenario provides a natural way to chain meaningful events and possible states...

An Extended KTH-Best Apprach for Referential-Uncooperative Bilevel Multi-Follower Decision Making

Guangquan Zhang, Chenggen Shi, Jie Lu
Pages: 205 - 214
Bilevel decision techniques have been mainly developed for solving decentralized management problems with decision makers in a hierarchical organization. When multiple followers are involved in a bilevel decision problem, called a bilevel multi-follower (BLMF) decision problem, the leader’s decision...

Support Vector Regression with Interval-Input Interval-Output

Wensen An, Cecilio Angulo, Yanguang Sun
Pages: 299 - 303
Support vector machines (classification and regression) are powerful machine learning techniques for crisp data. In this paper, the problem is considered for interval data. Two methods to deal with the problem using support vector regression are proposed and two new methods for evaluating performance...

Clustering feature vectors with mixed numerical and categorical attributes

R.k. Brouwer
Pages: 285 - 298
This paper describes a method for finding a fuzzy membership matrix in case of numerical and categorical features. The set of feature vectors with mixed features is mapped to a set of feature vectors with only real valued components with the condition that the new set of vectors has the same proximity...

Obstacle Avoidance of a Class of Underactuated Robot Manipulators: GA based approach

Qingbo Liu, Milan Zhang, Yueqing Yu, Shanzeng Liu
Pages: 353 - 360
This paper presents a practical collision-free motion planning method for general underactuated robot manipulators. First the dynamic properties of underactuated robot manipulator are analyzed, and then the collision avoidance problem is formulated and solved as a position-based force control problem....

Neural Network Based Traffic Prediction for Wireless Data Networks

Gowrishankar, P.s. Satyanarayana
Pages: 379 - 389
In a wireless network environment accurate and timely estimation or prediction of network traffic has gained much importance in the recent past. The network applications use traffic prediction results to maintain its performance by adopting its behaviors. Network Service provider will use the prediction...

Management of Uncertainty and Spatio-Temporal Aspects for Monitoring and Diagnosis in a Smart Home

Juan Carlos Augusto, Jun Liu, Paul Mccullagh, Hui Wang, Jian-bo Yang
Pages: 361 - 378
The health system in developed countries is facing a problem of scalability in order to accommodate the increased proportion of the elderly population. Scarce resources cannot be sustained unless innovative technology is considered to provide health care in a more effective way. The Smart Home provides...

Use of computational intelligence for the prediction of vacancy migration energies in atomistic kinetic monte carlo simulations

Nicolas Castin, Lorenzo Malerba, Roberto Pinheiro Domingos
Pages: 340 - 352
procedures for the calculation of point-defect migration energies in Atomistic Kinetic Monte Carlo (AKMC) simulations, as functions of the Local Atomic Configuration (LAC). Two approaches are considered: the Cluster Expansion (CE) and the Artificial Neural Network (ANN). The first is found to be unpromising...

An Image Based Approach to Compute Object Distance

Ashfaqur Rahman, Abdus Salam, Mahfuzul Islam, Partha Sarker
Pages: 304 - 312
Computing object distance using image processing is an important research area in the field of computer vision and robot navigation applications. In this paper we have proposed a new method to compute the distance of an object using a single image. According to our observation there exists a relationship...

Designing Structural Parameters of Nonwovens Using Fuzzy Logic and Neural Networks

Philippe Vroman, Ludovic Koehl, Xianyi Zeng, Ting Chen
Pages: 329 - 339
In this paper, a computer aided system for designing nonwoven materials is presented. As an original approach in the field of nonwoven research, both quality measurement analysis and human knowledge processing are integrated in the system. It allows designers to optimize the structure of nonwoven materials...

A Survey for Data Mining Framework for Polymer Matrix Composite Engineering Materials Design Applications

Hosahalli Doreswamy
Pages: 313 - 328
In this paper, a survey for Data Mining frame work has been done for proposing Data Mining methodologies to engineering materials design applications. An exhaustive literature survey made in this article has covered the modeling systems such as Analytical Model, Numerical Simulation Model and Computer...

On the Supply of Superior Order-1 Building Blocks for a Class of Periodical Fitness Functions

Hongqiang Mo Zhong Li
Pages: 91 - 98
In addition to GA-deception, the lack of fitness differences among low-order schemata can also degrade GA's search. Therefore, a coding should present adequate superior low-order building blocks at the early stage of search. This paper aims to reveal the inherent periodicity in the search process of...

Accuracy Evaluation of C4.5 and Naive Bayes Classifiers Using Attribute Ranking Method

S. Sivakumari, R. Praveena Priyadarsini, P. Amudha
Pages: 60 - 68
This paper intends to classify the Ljubljana Breast Cancer dataset using C4.5 Decision Tree and Nai?ve Bayes classifiers. In this work, classification is carriedout using two methods. In the first method, dataset is analysed using all the attributes in the dataset. In the second method, attributes...

Bacterial Foraging Optimized Hybrid Fuzzy Precompensated PD Control of Two Link Rigid-Flexible Manipulator

Srinivasan Alavandar, Tushar Jain, M. J. Nigam
Pages: 51 - 59
Light-weight flexible arms will most likely constitute the next generation robots due to their large payload carrying capacities at high speeds and less power demand. Control problem of robots with flexible members is more complex compared to rigid robots due to vibrations during the motion. This...

Reduct Driven Pattern Extraction from Clusters

Shuchita Upadhyaya, Alka Arora, Rajni Jain
Pages: 10 - 16
Clustering algorithms give general description of clusters, listing number of clusters and member entities in those clusters. However, these algorithms lack in generating cluster description in the form of pattern. From data mining perspective, pattern learning from clusters is as important as cluster...

Aumann Type Set-valued Lebesgue Integral and Representation Theorem

Jungang Li, Shoumei Li
Pages: 83 - 90
n this paper, we shall firstly illustrate why we should discuss the Aumann type set-valued Lebesgue integral of a set-valued stochastic process with respect to time t under the condition that the set-valued stochastic process takes nonempty compact subset of d -dimensional Euclidean space. After...

Support Vector Machines with Manifold Learning and Probabilistic Space Projection for Tourist Expenditure Analysis

Xin Xu, Rob Law, Tao Wu
Pages: 17 - 26
The significant economic contributions of the tourism industry in recent years impose an unprecedented force for data mining and machine learning methods to analyze tourism data. The intrinsic problems of raw data in tourism are largely related to the complexity, noise and nonlinearity in the data...

Video Classification and Shot Detection for Video Retrieval Applications

M. K. Geetha, S. Palanivel
Pages: 39 - 50
Appropriate organization of video databases is essential for pertinent indexing and retrieval of visual information. This paper proposes a new feature called Block Intensity Comparison Code (BICC) for video classification and an unsupervised shot change detection algorithm to detect the shot changes...

Feature Extraction for the Prognosis of Electromechanical Faults in Electrical Machines through the DWT

J.a. Antonino-daviu, M. Riera-guasp, M. Pineda-sanchez, J. Pons-llinares, R. Puche-panadero, J. Perez-cruz
Pages: 158 - 167
Recognition of characteristic patterns is proposed in this paper in order to diagnose the presence of electromechanical faults in induction electrical machines. Two common faults are considered; broken rotor bars and mixed eccentricities. The presence of these faults leads to the appearance of frequency...

Global Approximations to Cost and Production Functions using Artificial Neural Networks

Efthymios G. Tsionas, Panayotis G. Michaelides, Angelos T. Vouldis
Pages: 132 - 139
The estimation of cost and production functions in economics relies on standard specifications which are less than satisfactory in numerous situations. However, instead of fitting the data with a pre-specified model, Artificial Neural Networks (ANNs) let the data itself serve as evidence to support...

Networks of Mixed Canonical-Dissipative Systems and Dynamic Hebbian Learning

Julio Rodriguez, Max-olivier Hongler
Pages: 140 - 146
We study the dynamics of a network consisting of N diffusively coupled, stable-limit-cycle oscillators on which individual frequencies are parametrized by ωk , k = 1, . . . , N. We introduce a learning rule which influences the ωk by driving the system towards a consensual oscillatory state in...

The Influence of the Update Dynamics on the Evolution of the Cooperation

Carlos Grilo, Luis Correia
Pages: 104 - 114
We investigate the influence of the update dynamics on the evolution of cooperation. Three of the most studied games in this area are used: Prisoner’s Dilemma, Snowdrift and the Stag Hunt. Previous studies with the Prisoner’s Dilemma game reported that less cooperators survive with the asynchronous...

Cellular Neural Networks-Based Genetic Algorithm for Optimizing the Behavior of an Unstructured Robot

Alireza Fasih, Jean Chamberlain Chedjou, Kyandoghere Kyamakya
Pages: 124 - 131
A new learning algorithm for advanced robot locomotion is presented in this paper. This method involves both Cellular Neural Networks (CNN) technology and an evolutionary process based on genetic algorithm (GA) for a learning process. Learning is formulated as an optimization problem. CNN Templates...

Radial Basis Function Nets for Time Series Prediction

Abdelhamid Bouchachia
Pages: 147 - 157
This paper introduces a novel ensemble learning approach based on recurrent radial basis function networks (RRBFN) for time series prediction with the aim of increasing the prediction accuracy. Standing for the base learner in this ensemble, the adaptive recurrent network proposed is based on the...

Optimal IP Assignment for Efficient NoC-based System Implementation using NSGA-II and MicroGA

Marcus Vinicius Carvalho Da Silva, Nadia Nedjah, Luiza De Macedo Mourelle
Pages: 115 - 123
Network-on-chip (NoC) are considered the next generation of communication infrastructure, which will be omnipresent in most of industry, office and personal electronic systems. In platform-based methodology, an application is implemented by a set of collaborating intellectual properties (IPs) blocks....

A Hybrid Model for Forecasting Sales in Turkish Paint Industry

Alp Ustundag
Pages: 277 - 287
Sales forecasting is important for facilitating effective and efficient allocation of scarce resources. However, how to best model and forecast sales has been a long-standing issue. There is no best forecasting method that is applicable in all circumstances. Therefore, confidence in the accuracy...

Re-editing and Censoring of Detectors in Negative Selection Algorithm

X.z. Gao, S. J. Ovaska, X. Wang
Pages: 298 - 311
The Negative Selection Algorithm (NSA) is a kind of novelty detection method inspired by the biological self/nonself discrimination principles. In this paper, we propose two new schemes for the detectors re-editing and censoring in the NSA. The detectors that fail to pass the negative selection phase...