The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is conside...The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.展开更多
论述了功能、效应、知识3者之间的关系,提出了FEK(FEK:function-effect-knowledge)概念设计模型,以该模型为基础来构建传感器概念设计专家系统。首先采用关系数据库实现专家系统知识库;其次利用遗传算法优化效应链,建立效应模糊神经网...论述了功能、效应、知识3者之间的关系,提出了FEK(FEK:function-effect-knowledge)概念设计模型,以该模型为基础来构建传感器概念设计专家系统。首先采用关系数据库实现专家系统知识库;其次利用遗传算法优化效应链,建立效应模糊神经网络数学模型;最后用VS.NET和Microsoft SQL Server 2000作为前后台开发软件来开发传感器概念设计专家系统。所开发的专家系统运行良好,能够为传感器产品设计师在设计过程中提供启发性知识,但系统仍需不断地完善。展开更多
基金supported by proposal No.OSD/BCUD/392/197 Board of Colleges and University Development,Savitribai Phule Pune University,Pune
文摘The rapid developments in the fields of telecommunication, sensor data, financial applications, analyzing of data streams, and so on, increase the rate of data arrival, among which the data mining technique is considered a vital process. The data analysis process consists of different tasks, among which the data stream classification approaches face more challenges than the other commonly used techniques. Even though the classification is a continuous process, it requires a design that can adapt the classification model so as to adjust the concept change or the boundary change between the classes. Hence, we design a novel fuzzy classifier known as THRFuzzy to classify new incoming data streams. Rough set theory along with tangential holoentropy function helps in the designing the dynamic classification model. The classification approach uses kernel fuzzy c-means(FCM) clustering for the generation of the rules and tangential holoentropy function to update the membership function. The performance of the proposed THRFuzzy method is verified using three datasets, namely skin segmentation, localization, and breast cancer datasets, and the evaluated metrics, accuracy and time, comparing its performance with HRFuzzy and adaptive k-NN classifiers. The experimental results conclude that THRFuzzy classifier shows better classification results providing a maximum accuracy consuming a minimal time than the existing classifiers.
文摘论述了功能、效应、知识3者之间的关系,提出了FEK(FEK:function-effect-knowledge)概念设计模型,以该模型为基础来构建传感器概念设计专家系统。首先采用关系数据库实现专家系统知识库;其次利用遗传算法优化效应链,建立效应模糊神经网络数学模型;最后用VS.NET和Microsoft SQL Server 2000作为前后台开发软件来开发传感器概念设计专家系统。所开发的专家系统运行良好,能够为传感器产品设计师在设计过程中提供启发性知识,但系统仍需不断地完善。
