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检索条件"主题词=Inference Algorithms"

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Inductive learning from fuzzy examples

Inductive learning from fuzzy examples

引用

IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Ching-Hung Wang Tzung-Pei Hong Shian-Shyong Tseng Institute of Computer and Information Science National Chiao Tung University Taiwan Department of Information Management Kaohsiung Polytechnic Institute Taiwan

ISBN: (纸本)0780336453

In real applications, data provided to a learning system usually contain fuzzy information which greatly influences concept descriptions derived by conventional inductive learning methods. Modifying learning methods to learn concept descriptions in vague environments is thus very important. In this paper, we apply fuzzy set concept to machine learning to solve this problem. A fuzzy learning algorithm based on the version space strategy is proposed to manage fuzzy information. The proposed algorithm induces fuzzy linguistic inference rules from fuzzy instances, and finally infers outputs based on the fuzzy rules derived and user inputs. The Iris flower classification problem is used to compare the accuracy of the proposed algorithm with that of some other learning algorithms. Experimental results show that our method yields high accuracy.

关键词： Fuzzy sets inference algorithms Iris Machine learning algorithms Learning systems Fuzzy systems Information management Machine learning Working environment noise Law

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Query answering using discovered rules

Query answering using discovered rules

引用

International Conference on Data Engineering

作者： I.-M.A. Chen Data Management Research & Development Group Information and Computing Sciences Division Lawrence Berkeley National Laboratory Berkeley CA USA

Research has been done in discovering rules from databases and in applying these rules to intensional answers to database queries, semantic query optimization, etc. However, rules discovered by one group of users may not be used by other groups of users in their applications due to certain mismatches. In this paper, we address the problems of using discovered rules for query answering, and then propose algorithms for rewriting, applying and maintaining these rules.

关键词： Databases Data mining EMP radiation effects Remuneration Research and development management Laboratories Machine learning Query processing Forward contracts inference algorithms

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Processing of semantic information in fluently spoken language

Processing of semantic information in fluently spoken langua...

引用

International Conference on Spoken Language, ICSLP

作者： A.L. Gorin AT and T Research Murray Hill NJ USA

We are interested in constructing machines which learn to understand and act upon fluently spoken input. For any particular task, certain linguistic events are critical to recognize correctly, others not so. This notion can be quantified via salience, which measures the information content of an event for a task. In previous papers, salient words have been exploited to team the mapping from spoken input to machine action for several tasks. In this work, a new algorithm is presented which automatically acquires salient grammar fragments for a task, exploiting both linguistic and extra-linguistic information in the inference process. Experimental results are reported for a database of fluently spoken customer requests to operators, responding to the open-ended prompt, 'Hello, this is AT&T. How may I help you?'.

关键词： Natural languages Databases inference algorithms Vocabulary Humans Data mining Predictive models Automatic speech recognition Buildings Grounding

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A pseudo outer-product based fuzzy neural network and its rule-identification algorithm

A pseudo outer-product based fuzzy neural network and its ru...

引用

International Conference on Neural Networks

作者： R.W. Zhou C. Quek SAS Nanyang Technological University Singapore

A novel fuzzy neural network, called the pseudo outer-product based fuzzy neural network (POPFNN), is proposed in this paper. Similar to most existing fuzzy neural networks, the proposed POPFNN uses a self-organizing algorithm to learn and initialize the membership functions of the input and output variables from a set of training data. However, instead of employing the commonly used competitive learning, we proposed a novel one-pass lazy pseudo outer-product (LazyPOP) learning algorithm to identify the fuzzy rules that are supported by the training data. In contrast with other rule-identification algorithms the proposed LazyPOP learning algorithm is fast, reliable, and highly intuitive. Extensive experimental results and comparisons are presented.

关键词： Fuzzy neural networks Fuzzy systems Neural networks Training data inference algorithms Organizing Neurons Synthetic aperture sonar Fuzzy logic Equations

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A method of learning implication networks from empirical data: algorithms and Monte Carlo simulation based validation

A method of learning implication networks from empirical dat...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Jiming Liu M.C. Desmarais Y.Y. Tang Department of Computing Studies Hong Kong Baptist University Kowloon Hong Kong China Computer Research Institute of Montreal QUE Canada

This paper describes an algorithmic method of inducing implication networks from empirical data samples and reports some validation results with this method. The induced network enables efficient inferences about the values of network nodes given certain observations. This implication induction method is approximate in nature as probabilistic network requirements are relaxed in the construction of dependence relationships based on statistical testing. In order to examine the validity of the induced networks, several Monte Carlo simulations were conducted where predefined Bayesian networks were used to generate empirical data samples-some of which were used to induce implication relations whereas others were used to verify the results of evidential reasoning in the induced networks. The valves in the implication networks were predicted by applying a modified version of the Dempster-Shafer belief updating scheme. The results of predictions were, furthermore, compared to the ones generated by Pearl's stochastic simulation method, a probabilistic reasoning method that operates directly on the predefined Bayesian networks. The comparisons consistently show that the results of predictions based on the induced networks would be comparable to those generated by Pearl's method when reasoning in a variety of uncertain knowledge domains.

关键词： Bayesian methods Stochastic processes Computer networks inference algorithms Statistical analysis Monte Carlo methods Induction generators Predictive models Optimized production technology Marine vehicles

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Double description and separate identification of nonlinear multi-variable systems

Double description and separate identification of nonlinear ...

引用

IEEE International Conference on Systems, Man and Cybernetics

作者： Jianguo Han Xiangyu Wei Yuming Li Yanshan Lu Beijing University of Chemical and Technology Beijing China

In the paper, a method of model description and identification of nonlinear multi-variable systems based on applying conventional identification as well as an artificial neural network is suggested. An on-line and rea... 详细信息

ISBN: (纸本)0780332806

关键词： inference algorithms Artificial neural networks Heating Fuzzy neural networks Chemical technology System identification Real time systems Automation Algorithm design and analysis Electrical capacitance tomography

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Supervisory control for elevator group by using fuzzy expert system which addresses the riding time

Supervisory control for elevator group by using fuzzy expert...

引用

International Conference on Industrial Electronics, Control and Instrumentation

作者： Y. Sogawa T. Ishikawa K. Igarashi Graduate school Musashi Institute of Technology Tokyo Japan Technological Development of Information Processing Company Limited Tokyo Japan

There are two algorithms in the conventional elevator group control system: the minimum long-wait algorithm and the area-based control algorithm. These algorithms are designed to reduce service time (waiting time+riding time) by decreasing waiting time. This article proposes a new elevator group control system which addresses riding time as well as waiting time. It is difficult to tell the user's destination floor at the point of elevator car assignment. The authors decided, therefore, to design the algorithm in a way not to increase the user's riding time in order to reduce service time and improve the overall services to users.

关键词： Supervisory control Elevators Hybrid intelligent systems Algorithm design and analysis inference algorithms Fuzzy systems Floors Educational institutions Control systems Expert systems

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Finite automata based compression of bi-level images

Finite automata based compression of bi-level images

引用

Data Compression Conference (DCC)

作者： K. Culik V. Valenta Department of Computer Science University of South Carolina Columbia SC USA

We introduce generalized finite automata as a tool for specification of bi-level images. We describe an inference algorithm for generalized finite automata and a lossy compression system for bi-level images based on t... 详细信息

关键词： Automata Image coding inference algorithms Image resolution Decoding Computer science Vector quantization Image recognition Image quality Gray-scale

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Refining image compression with weighted finite automata

Refining image compression with weighted finite automata

引用

Data Compression Conference (DCC)

作者： U. Hafner Lehrstuhl für Informatik II Universität WÜrzburg Germany

Weighted finite automata (WFA) generalize finite automata by attaching real numbers as weights to states and transitions. As shown by Culik and Kari (1994, 1995) WFA provide a powerful tool for image generation and compression. The inference algorithm for WFA subdivides an image into a set of nonoverlapping range images and then separately approximates each one with a linear combination of the domain images. In the current paper we introduce an improved definition for WFA that increases the approximation quality significantly, clearly outperforming the JPEG image compression standard. This is achieved by the bintree partitioning of the image and by appending not only two adjacent range images but also every single range image to the pool of domain images. Moreover, we present a new lossless entropy coding module that achieves efficient and fast storing and retrieving of the WFA coefficients.

关键词： Image coding Automata Codecs Joining processes Image generation inference algorithms Transform coding Entropy coding Image retrieval Code standards

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Pattern matching in search problem solving

Pattern matching in search problem solving

引用

Annual Hawaii International Conference on System Sciences (HICSS)

作者： M. Stanojevic S. Vranes D. Velasevic Mihajlo Pupin Institut Belgrade Serbia The Faculty of Electrical Engineering Belgrade Serbia

Search problems generally fall into the class of NP hard problems. Many real problems including planning, diagnosing, allocation tasks, classification tasks and scenario making, require examination of large search spaces. These problems cannot be solved directly (i.e., without searching) by simply applying the appropriate algorithms. Expert systems are usually applied to solve different search problems. However, only a few expert systems with the truth maintenance capability are able to solve them efficiently. A truth maintenance system is used to organize data into data abstractions that represent points in search spaces, and also to maintain data consistency, while the inference engine is used to examine problem states and to guide the search process. Knowing that expert systems spend about 90% of their time in each recognize-act cycle performing pattern matching, it is obvious that the pattern matching algorithm represents one of the most critical components of the inference engine. Two of the most popular pattern matching algorithms TREAT and RETE, are applied in almost all expert systems. Although these algorithms are very efficient in applications which do not require the examination of search spaces, they perform some futile work in search problem solving. We propose a pattern matching algorithm, specially tuned for the solution of search problems, which override the drawbacks of TREAT and RETE algorithms and increases the efficiency of the overall system.

关键词： Search problems inference algorithms Expert systems Engines Diagnostic expert systems Pattern matching NP-hard problem Pattern recognition Artificial intelligence Path planning

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