In this paper, genetic algorithms and machine learning theory and method of knowledge acquisition for expert system structure is proposed to solve the "bottleneck" problems in the traditional machine learning methods on the basis of AQ, the model of knowledge acquisition based on GA is proposed and its application is used in the Fish Disease Diagnosis reasoning system, the rules is accessed to ...

â â â  â â â  nowadays, the world economies are rapidly moving towards being more knowledge-based economy (kbe) and supporting the force of knowledge as a vital component of economic growth. this recent acceleration in the transition to knowledge-based economy in the world, has affected regional economic performance. in this paper, we surveyed the regional convergence in knowledge-based economy...

This paper considers the job scheduling problem in virtual manufacturing cells (VMCs) with the goal of minimizing two objectives namely, makespan and total travelling distance. To solve this problem two algorithms are proposed: traditional non-dominated sorting genetic algorithm (NSGA-II) and knowledge-based non-dominated sorting genetic algorithm (KBNSGA-II). The difference between these algor...

Image understanding systems rely heavily on a priori knowledge of their application domain, often exploiting techniques developed in the wider field of knowledge-based systems (KBSs). Despite attempts, typified by the KADS/CommonKADS projects, to develop structured knowledge engineering approaches to KBS development, those working in image understanding continue to employ unstructured 1 generat...

Knowledge management depends on effective methods for capturing knowledge in useful forms and making it available when needed. Electronic concept maps provide a promising representation for knowledge models that can be developed directly by the experts themselves, but the flexibility of concept mapping raises questions of how to support the knowledge modeling process and to standardize its resu...

This paper addresses methods of knowledge engineering for chemical and biochemical process modelling and control. The concept of Knowledge Based Modular (KBM) Networks is presented. KBM networks represent a method of expressing and combining different types of knowledge, usually available for modelling chemical and biochemical processes: mechanistic, heuristic and knowledge hidden in process da...

Computer based learning gets more and more important in higher education. Particularly, in Legal domain, students have little chance to deal with realistic situations. One way to alleviate this problem is to provide Law students with real cases, rules and different viewpoints of which a given body of knowledge is often recognized as important to their successful learning. We propose a novel app...

This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

The definition of similarity measures—one core component of each CBR application—leads to a serious knowledge acquisition problem if domain and application specific requirements have to be considered. To reduce the knowledge acquisition effort, different machine learning techniques have been developed in the past. In this paper, enhancements of our framework for learning knowledge-intensive sim...