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Implementation of Web-Based Chilli Expert Advisory System Using ABC Optimization Algorithm

机译:基于ABC优化算法的基于Web的辣椒专家咨询系统的实现

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The presently developed paper deals with the concepts of web based online expert systems and machine learning Algorithms in the field of Artificial Intelligence. An expert system follows the methodology of task-based specification and it is independent in case of problem solving. Where as, the machine learning technique is used to find the good optimal solution. This paper mainly focuses on the investigations on the diseases and treatment to the diseases which were effected to the chilli plants by using the mechanism of Rule based system and Artificial Bee Colony1 (ABC) algorithm. The rules in the database is processed by the rule based system and if the required rules are not present in the database, then the system goes to the Machine learning algorithm technique used expert system. Thus, by applying machine learning techniques, resulting to best global optimized solution for recognizing the diseases in chilli plants. This expert system is a web based online application for online users with java as front end and MySQL as backend.
机译:目前开发的论文涉及人工智能领域中基于Web的在线专家系统和机器学习算法的概念。专家系统遵循基于任务的规范的方法,并且在解决问题的情况下是独立的。在那里,使用机器学习技术来找到良好的最佳解决方案。利用基于规则的系统机制和人工蜂群算法(ABC),对辣椒植物的病害及其治疗方法进行了研究。数据库中的规则由基于规则的系统处理,如果数据库中不存在所需的规则,则系统将使用专家系统使用的机器学习算法技术。因此,通过应用机器学习技术,获得了用于识别辣椒植物中疾病的最佳全局最佳解决方案。该专家系统是一个基于Web的在线应用程序,适用于以java为前端,以MySQL为后端的在线用户。

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