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REFERENCE LINKING PLATFORM OF KOREA S&T JOURNALS
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Journal of Korean Institute of Intelligent Systems
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Korean Institute of Intelligent Systems
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Volume & Issues
Volume 11, Issue 9 - Dec 2001
Volume 11, Issue 8 - Dec 2001
Volume 11, Issue 7 - Dec 2001
Volume 11, Issue 6 - Dec 2001
Volume 11, Issue 5 - Oct 2001
Volume 11, Issue 4 - Aug 2001
Volume 11, Issue 3 - Jun 2001
Volume 11, Issue 2 - Apr 2001
Volume 11, Issue 1 - Feb 2001
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Genetic Algorithms based on Maintaining a diversity of the population for Job-shop Scheduling Problem
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 191~199
This paper presents a new genetic algorithm for job-shop scheduling problems. When we design a genetic algorithm for difficult ordering problems such as job-shop scheduling problems, it is important to design encoding/crossover that is excellent in characteristic preservation and to maintain a diversity of population. We used Job-based order crossover(JOX). Since the schedules generated by JOX are not always active-schedule, we proposed a method to transform them into active schedulesby using the GT method with c)laracteristic preservation. We introduce strategies for maintaining a diversity of the population by eliminating same individuals in the population. Furthermore, we are not used mutation. Experiments have been done on two examples: Fisher s and Thompson s
A Segmentation-Based HMM and MLP Hybrid Classifier for English Legal Word Recognition
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 200~207
In this paper, we propose an HMM(Hidden Markov modeJ)-MLP(Multi-layer perceptron) hybrid model for recognizing legal words on the English bank check. We adopt an explicit segmentation-based word level architecture to implement an HMM engine with nonscaled and non-normalized symbol vectors. We also introduce an MLP for implicit segmentation-based word recognition. The final recognition model consists of a hybrid combination of the HMM and MLP with a new hybrid probability measure. The main contributions of this model are a novel design of the segmentation-based variable length HMMs and an efficient method of combining two heterogeneous recognition engines. ExperimenLs have been conducted using the legal word database of CENPARMI with encouraging results.
Design of Fuzzy Controller for Input-delayed TS Fuzzy Systems
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 208~214
Neural Network Structure and Parameter Optimization via Genetic Algorithms
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 215~222
Neural network based models of semiconductor manufacturing processes have been shown to offer advantages in both accuracy and generalization over traditional methods. However, model development is often complicated by the fact that back-propagation neural networks contain several adjustable parameters whose optimal values unknown during training. These include learning rate, momentum, training tolerance, and the number of hidden layer neurOnS. This paper presents an investigation of the use of genetic algorithms (GAs) to determine the optimal neural network parameters for the modeling of plasma-enhanced chemical vapor deposition (PECVD) of silicon dioxide films. To find an optimal parameter set for the neural network PECVD models, a performance index was defined and used in the GA objective function. This index was designed to account for network prediction error as well as training error, with a higher emphasis on reducing prediction error. The results of the genetic search were compared with the results of a similar search using the simplex algorithm.
Optimization of Structure-Adaptive Self-Organizing Map Using Genetic Algorithm
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 223~230
Since self-organizing map (SOM) preserves the topology of ordering in input spaces and trains itself by unsupervised algorithm, it is Llsed in many areas. However, SOM has a shortcoming: structure cannot be easily detcrmined without many trials-and-errors. Structure-adaptive self-orgnizing map (SASOM) which can adapt its structure as well as its weights overcome the shortcoming of self-organizing map: SASOM makes use of structure adaptation capability to place the nodes of prototype vectors into the pattern space accurately so as to make the decision boundmies as close to the class boundaries as possible. In this scheme, the initialization of weights of newly adapted nodes is important. This paper proposes a method which optimizes SASOM with genetic algorithm (GA) to determines the weight vector of newly split node. The leanling algorithm is a hybrid of unsupervised learning method and supervised learning method using LVQ algorithm. This proposed method not only shows higher performance than SASOM in terms of recognition rate and variation, but also preserves the topological order of input patterns well. Experiments with 2D pattern space data and handwritten digit database show that the proposed method is promising.
A Study on the Self-Evolving Expert System using Neural Network and Fuzzy Rule Extraction
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 231~240
Conventional expert systems has been criticized due to its lack of capability to adapt to the changing decision-making environments. In literature, many methods have been proposed to make expert systems more environment-adaptive by incorporating fuzzy logic and neural networks. The objective of this paper is to propose a new approach to building a self-evolving expert system inference mechanism by integrating fuzzy neural network and fuzzy rule extraction technique. The main recipe of our proposed approach is to fuzzify the training data, train them by a fuzzy neural network, extract a set of fuzzy rules from the trained network, organize a knowledge base, and refine the fuzzy rules by applying a pruning algorithm when the decision-making environments are detected to be changed significantly. To prove the validity, we tested our proposed self-evolving expert systems inference mechanism by using the bankruptcy data, and compared its results with the conventional neural network. Non-parametric statistical analysis of the experimental results showed that our proposed approach is valid significantly.
Design of the Fuzzy Traffic Controller by the Input-Output Data Clustering
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 241~245
The existing fuzzy traffic controllers construct the rule-base based on the intuitive knowledge and experience or the standard rule-base, but the rule-base constructed by the above methods has difficulty in representing exactly and detailedly the control knowledge of the export and the operator. Therefore, in this paper, we propose a method that can improve the performance of the fuzzy traffic control by designing the fuzzy traffic controller which represents the control knowledge more exactly. The proposed method so modifies the position and shape of the fuzzy membership function based on the input-output data clustering that the fuzzy traffic controller can represent the control knowledge more exactly. Our method use the rough control knowledge based on intuitive knowledge and experience as the evaluation function for clustering the input-output data. The fuzzy traffic controller designed by the our method could represent the control knowledge of the expert and the operator more exactly, and it outperformed the existing controller in terms of the number of passed vehicles and the wasted green-time.
Fuzzy Theory based Electronic Commerce Navigation Agent that can Process Natural Language
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 246~251
In this paper, we proposed the intelligent navigation agent model for successive electronic commerce system management. Fuzzy theory is very useful method where keywords have vague conditions and system must process that conditions. So, using fuzzy theory, we proposed the model that can process the vague keywords effectively. Through the this, we verified that we can get the more appropriate navigation result than any other crisp retrieval keywords condition.
A Study on Information Retrieval Using Query Splitting Relevance Feedback
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 252~257
In conventional boolean retrieval systems, document ranking is not supported and similarity coefficients cannot be computed between queries and documents. The MMM, Paice and P-norm models have been proposed in the past to support the ranking facility for boolean retrieval systems. They have common properties of interpreting boolean operators softly. In this paper we propose a new soft evaluation method for Information retrieval using query splitting relevance feedback model. We also show through performance comparison that query splitting relevance feedback(QSRF) is more efficient and effective than MMM, Paice and P-norm.
Detecting fingerprint features with immediate adaptation to local fingerprint quality using fuzzy logic
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 258~263
This paper complements the shortcomings of the original edge following algorithm. We propose a new edge following method which exploits the uncertainty residing in fingerprint analysis. Based on fuzzy set theory, the proposed algorithm computes the current local quality of a fingerplinL image by considering two Jocal properties: a relative cardinality of fuzzy set and a local variance. According to the calculated local quality infonnation, we dynamically adopt the appropriate different methods.
Fuzzy Logic-based Modeling of a Score
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 264~269
In this paper, we interpret a score as a time series and deal with the fuzzy logic-based modeling of it. The musical notes in a score represent a lot of information about the length of a sound and pitches, etc. In this paper, using melodies, tones and pitches in a score, we transform data on a score into a time series. Once more, we foml the new Lime series by sliding a window through the time series. For analyzing the time series data, we make use of the Box-Jenkins s time series analysis. On the basis of the identified characteristics of time series, we construct the fuzzy model.
A similarity measure of fuzzy sets
Kwon, Soon H. ;
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 270~274
Conventional similarity measures suggested so far can be classified into three categories: (i) geometric similarity measures, (ij) set-theoretic similarity measures, and (iii) matching function-based similarity measures. On the basis of the characteristics of the conventional similarity measures, in this paper, we propose a new similarity measure of fuzzy sets and investigate its properLies. Finally, numelical examples are provided for the comparison of characteristics of the proposed similarity measure and other previous similarity measures.
Fuzzy Strongly r-Semineighborhoods
Lee, Seok-Jong ; Lee, Seung-On ; Park, Ju-Hui ;
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 275~279
In this thesis, we introduce and investigate the notions of a fuzzy strongly r-semineighborhood and a fuzzy strongly r-quasi-semineighborhood in fuzzy topological spaces which are generalizations of a fuzzy strongly semineighborhood and a fuzzy strongly quasi-semineighborhood, respectively.
Some Fuzzy Continuous Mappings and Fuzzy Mildly Normal Spaces
Ahn, Y. S. ; Choi, K. H. ; Hur, K. ;
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 280~285
We introduce the new concepts of some fuzzy continuous and closed mappings and study their properties. Also we investigate the properties of fuzzy mildly normal spaces.
Some Properties of BL-Algebras
Ko, Jung-Mi ; Kim, Yong-Chan ;
Journal of Korean Institute of Intelligent Systems, volume 11, issue 3, 2001, Pages 286~291
We inverstigate the properties of BL-hommorphisms on BL-algebras. In particular, we find the BL-algebra in duced by lattice-isomorphism. From these facts, we obtain the generalized Lukasiewicz structure. More-over, we study the properties of quotient BL-algebras and deductive systems.