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JAI Introduction 认领 引用
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《Journal of Automation and Intelligence》 CSCD 2025年第1期F0002-F0002,共1页
Artificial intelligence(AI) is almost everywhere due to the rapid development of modern technology and popularity of intelligent devices.While control theory and machine learning techniques as two enabling technologie... Artificial intelligence(AI) is almost everywhere due to the rapid development of modern technology and popularity of intelligent devices.While control theory and machine learning techniques as two enabling technologies have shown enormous power in their own right,a rapprochement of them is required to handle nonlinearity,uncertainty and scalability induced by high complexity of modern systems,huge quantity of real-time data,and large scale of agent networks. 展开更多
关键词 control theory machinelearning techniques artificial intelligence al intelligent deviceswhile controltheory nonlinearity machinlearning modern technology agent networks
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Software design pattern mining using classification-based techniques 认领 引用 被引量：8
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作者 Ashish Kumar DWIVEDI Anand TIRKEY Santanu Kumar RATH 《Frontiers of Computer Science》 SCIE EI CSCD 2018年第5期908-922,共15页
Design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to t... Design patterns are often used in the development of object-oriented software. It offers reusable abstract information that is helpful in solving recurring design problems. Detecting design patterns is beneficial to the comprehension and maintenance of object-oriented software systems. Several pattern detection techniques based on static analysis often encounter problems when detecting design patterns for identical structures of patterns. In this study, we attempt to detect software design patterns by using software metrics and classification-based techniques. Our study is conducted in two phases： creation of metrics-oriented dataset and detection of software design patterns. The datasets are prepared by using software metrics for the learning of classifiers. Then, pattern detection is performed by using classification-based techniques. To evaluate the proposed method, experiments are conducted using three open source software programs, JHotDraw, QuickUML, and JUnit, and the results are analyzed. 展开更多
关键词 design patterns design pattern mining machinelearning techniques object-oriented metrics
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