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Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems最新文献

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Lagrangian method for wire routing of layout design 拉格朗日法布线设计
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499506
M. Nagamatu, S. Ismail, T. Yanaru
{"title":"Lagrangian method for wire routing of layout design","authors":"M. Nagamatu, S. Ismail, T. Yanaru","doi":"10.1109/ANNES.1995.499506","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499506","url":null,"abstract":"In this paper, we propose a new algorithm which solves the routing problem of LSI layout design as a continuous valued constrained optimization problem. All continuous valued wires change their values simultaneously according to the dynamic equations of Lagrangian method, hence this method is suitable for neurocomputing. We show that this method can solve the small switchbox routing problems with a higher completion rate as compared to the rip-up reroute maze router.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114906382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Bandsaw diagnostics by neurocomputing-two are better than one! 神经计算的带锯诊断——两个总比一个好!
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499501
D. Tuck
{"title":"Bandsaw diagnostics by neurocomputing-two are better than one!","authors":"D. Tuck","doi":"10.1109/ANNES.1995.499501","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499501","url":null,"abstract":"In industrial sawmills, bandsaws must work at a high production rate. Two major factors which limit cutting performance are cracking and instability of the saw blades. This paper describes the results from the development of a diagnostic system which monitors blade vibration and blade tension sensor data to estimate crack length using neurocomputing techniques, to help predict blade failure. It was found that a multi-layered feedforward artificial neural network with two hidden layers produces the most reliable results. The results indicate that this system should enable the detection of cracking in blades while in a running but unloaded (between cuts) state. This may help allow longer run times to be planned with confidence increasing production uptime and minimising maintenance.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114128033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Neurocomputing for large-scale design automation 大规模设计自动化的神经计算
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499491
H. Adeli
{"title":"Neurocomputing for large-scale design automation","authors":"H. Adeli","doi":"10.1109/ANNES.1995.499491","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499491","url":null,"abstract":"The author and his associates have been working on creating novel design theories and computational models with two broad objectives: automation and optimization. The paper is a summary of research done by the author and his associates recently. Novel neurocomputing algorithms are presented for large scale design optimization. This research demonstrates how a new level is achieved in design automation through the ingenious use and integration of a novel computational paradigm, mathematical optimization, and new high performance computer architecture.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127913420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Constructing a high performance signature verification system using a GA method 利用遗传算法构建高性能签名验证系统
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499465
Xuhua Yang, T. Furuhashi, K. Obata, Y. Uchikawa
{"title":"Constructing a high performance signature verification system using a GA method","authors":"Xuhua Yang, T. Furuhashi, K. Obata, Y. Uchikawa","doi":"10.1109/ANNES.1995.499465","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499465","url":null,"abstract":"To realize a high-peformance automatic signature verification system, it is necessary that the selected features are potentially difficult to imitate. One of the advantages of online signature verification is that the virtual strokes which are left in the pen-up situation can be obtained. These virtual strokes can be memorized by the computer but are invisible to humans. So there is little possibility of imitating these strokes deliberately. The features included in such strokes are expected to realize a high verification performance. This paper proposes to find the optimal features for signature verification from these virtual strokes by using a genetic algorithm (GA). Experiments are carried out to show the effectiveness of the new method.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131827815","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 27
A neural architecture for fast rule matching 一种快速规则匹配的神经网络结构
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499484
J. Austin, J. Kennedy, K. Lees
{"title":"A neural architecture for fast rule matching","authors":"J. Austin, J. Kennedy, K. Lees","doi":"10.1109/ANNES.1995.499484","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499484","url":null,"abstract":"This paper describes a simple neural architecture that can be used to match rules in knowledge based systems. The approach allows very large numbers of rules to be searched and matched using simple neural correlation matrix memories. The architecture is specifically designed to cope with inputs that may contain errors or be incomplete. Because the neural architecture is based on binary inputs and binary weights it is particularly applicable to fast operation on standard computers as well as specialized hardware. The paper describes the current implementation of the system, its advantages compared to other methods and the motivation that led to its design.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130476645","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 22
Case-based reasoning with spatial data 基于案例的空间数据推理
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499514
A. Holt, G. Benwell
{"title":"Case-based reasoning with spatial data","authors":"A. Holt, G. Benwell","doi":"10.1109/ANNES.1995.499514","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499514","url":null,"abstract":"This paper outlines the adaption of artificial intelligence techniques in spatial information systems. This adaption improves the analytical strength of spatial information systems. This paper includes a discussion of previously coupled techniques such as expert systems, fuzzy logic, hybrid connection systems and neural networks. It proposes a spatial reasoning prototype which is a based upon the integration of case-based reasoning and spatial information systems techniques.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130752782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 4
The development of Holte's 1R classifier 霍尔特1R分类器的发展
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499480
C. Nevill-Manning, G. Holmes, I. Witten
{"title":"The development of Holte's 1R classifier","authors":"C. Nevill-Manning, G. Holmes, I. Witten","doi":"10.1109/ANNES.1995.499480","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499480","url":null,"abstract":"The 1R machine learning scheme (Holte, 1993) is a very simple one that proves surprisingly effective on the standard datasets commonly used for evaluation. This paper describes the method and discusses two aspects of the algorithm that bear further analysis: the way, that intervals are formed when discretizing continuously-valued attributes; and the way missing values are treated. We then show how the algorithm can be extended to avoid a problem endemic to most practical machine learning algorithms-their frequent dismissal of an attribute as irrelevant when in fact it is highly relevant when combined with other attributes.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122212117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 33
On performance measures of artificial neural networks trained by structural learning algorithms 结构学习算法训练的人工神经网络性能度量研究
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499430
R. Kozma, M. Kitamura, A. Malinowski, J. Zurada
{"title":"On performance measures of artificial neural networks trained by structural learning algorithms","authors":"R. Kozma, M. Kitamura, A. Malinowski, J. Zurada","doi":"10.1109/ANNES.1995.499430","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499430","url":null,"abstract":"Structural learning in multi layer, feedforward neural networks was studied using M. Ishikawa's (1994) modified backpropagation algorithm with forgetting of the connection weights. The proper choice of forgetting constant was investigated previously but no generally accepted method has been established yet. The generalization rate of the trained network is analyzed as a possible means of selecting optimum model parameters. The results are illustrated using R.A. Fisher's (1936) IRIS data and anomaly detection in time series.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123765631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
An approach to design fuzzy IF-THEN rules for fuzzy-controlled static VAr compensator 模糊控制静态无功补偿器的模糊IF-THEN规则设计方法
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499453
T. Yamakawa, E. Uchino, T. Miki, M. Takayama
{"title":"An approach to design fuzzy IF-THEN rules for fuzzy-controlled static VAr compensator","authors":"T. Yamakawa, E. Uchino, T. Miki, M. Takayama","doi":"10.1109/ANNES.1995.499453","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499453","url":null,"abstract":"The paper describes an approach to design fuzzy IF-THEN rules for the fuzzy-controlled static VAr compensator (FCSVC) in a three-phase electric power system. In general, designing fuzzy IF-THEN rules for fuzzy-controlled non-linear MIMO systems is very difficult because the system is too complex to obtain the knowledge of experts sufficiently. Therefore, automatic design of the rules from input-output data is studied by many researchers. However, it is impossible to apply the designing method to the FCSVC in a three-phase electric power system because the system is so dynamic and the input-output data are not obtained completely. We propose a FCSVC, the rules of which are designed more easily and more efficiently and depend on the condition of the system. The effectiveness of the approach described in the paper is verified by the experimental results.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"122 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128493727","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
A genetic-based method for learning the parameters of a fuzzy inference system 基于遗传的模糊推理系统参数学习方法
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems Pub Date : 1995-11-20 DOI: 10.1109/ANNES.1995.499476
Florin Fagarasan, M. Negoita
{"title":"A genetic-based method for learning the parameters of a fuzzy inference system","authors":"Florin Fagarasan, M. Negoita","doi":"10.1109/ANNES.1995.499476","DOIUrl":"https://doi.org/10.1109/ANNES.1995.499476","url":null,"abstract":"Fuzzy inference systems (FIS) provide models for approximating continuous, real valued functions. The successful application of fuzzy reasoning models depends on a number of parameters, such as the fuzzy partition of the input/output universes of discourse, that are usually decided in a subjective manner (traditionally, fuzzy rule bases are constructed by knowledge acquisition from human experts). This paper presents a flexible genetic based method for learning the parameters of a FIS from examples such as the subjectivity not to be involved at all. We show that applying this method it is possible to obtain better performances for the FIS or, for the same performances, a less complex structure for the system.","PeriodicalId":123427,"journal":{"name":"Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131021925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 6
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