{"title":"Hybrid model of general fuzzy automata and semantic computing: an application to transportation e-service","authors":"Ranjeet Kaur, Alka Tripathi","doi":"10.1007/s00500-024-09829-2","DOIUrl":null,"url":null,"abstract":"<p>The computing models such as crisp automata, fuzzy automata and general fuzzy automata (GFA) are used to represent complex systems for predefined input alphabets or symbols. A framework that can process words rather than symbols is needed to simulate applications based on the natural language. Semantic computing (SC) offers a technique to accommodate semantically similar words instead of predefined words, thus extends the applicability and flexibility of GFA. In present work, a hybrid model of GFA and SC is proposed to deal with a situation where input can be user-dependent or related to words that have semantically similar meanings. In traditional theory of automata, if input symbols are changed one must define a new automata, whereas in the proposed work instead of defining a new GFA, existing GFA can process the semantically similar external words. An application related to transportation e-service is further discussed to understand the enhanced flexibility and applicability of the proposed models.</p>","PeriodicalId":22039,"journal":{"name":"Soft Computing","volume":"51 1","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s00500-024-09829-2","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
The computing models such as crisp automata, fuzzy automata and general fuzzy automata (GFA) are used to represent complex systems for predefined input alphabets or symbols. A framework that can process words rather than symbols is needed to simulate applications based on the natural language. Semantic computing (SC) offers a technique to accommodate semantically similar words instead of predefined words, thus extends the applicability and flexibility of GFA. In present work, a hybrid model of GFA and SC is proposed to deal with a situation where input can be user-dependent or related to words that have semantically similar meanings. In traditional theory of automata, if input symbols are changed one must define a new automata, whereas in the proposed work instead of defining a new GFA, existing GFA can process the semantically similar external words. An application related to transportation e-service is further discussed to understand the enhanced flexibility and applicability of the proposed models.
期刊介绍：
Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems.
Soft Computing encourages the integration of soft computing techniques and tools into both everyday and advanced applications. By linking the ideas and techniques of soft computing with other disciplines, the journal serves as a unifying platform that fosters comparisons, extensions, and new applications. As a result, the journal is an international forum for all scientists and engineers engaged in research and development in this fast growing field.
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