Several researchers initiated their work of models and framework development by creating evaluation criteria (also called success criteria or quality aspects). These criteria not only guided development but also were used to help evaluate their models and frameworks. This paper reviews Boehm’s evaluation criteria for assessing a cost model, Beecham’s success criteria for validating a Requiremen...

abstract evapotranspiration as one of the important elements in agriculture has a considerable role in water resource management. therefore, using a more exact estimation method is an essential step of agricultural development, especially in arid semi-arid area. in this research, in order to exact estimate of garlic evapotranspiration using lysimeteric data, an artificial neural network (ann) m...

In this paper we present an evaluation of rule-based morphological components for German for use in an interactive editing environment. The criteria for the evaluation are deduced from the intended use of these components, namely availability, performance, programming interfaces, and analysis quality. We evaluated systems developed and maintained since decades as well as new systems. However, w...

This study examines a Kansei retrieval agent (KaRA) model based on fuzzy reasoning in terms of optimizing rules. The KaRA learns the user’s preferences sensory evaluation, and retrieves what user wants from large amount data. has information membership functions Previous studies have demonstrated effectiveness learning evaluation criteria by function using numerical simulation. However, rules n...

In this paper, we propose a rule-based formalization of eligibility criteria for clinical trials. The rule-based formalization is implemented by using the logic programming language Prolog. Compared with existing formalizations such as pattern-based and scriptbased languages, the rule-based formalization has the advantages of being declarative, expressive, reusable and easy to maintain. Our rul...

In this paper, we present an evaluation of a rule evaluation support method for post-processing of mined results with rule evaluation models based on objective indices. To reduce the costs of rule evaluation task, which is one of the key procedures in data mining post-processing, we have developed the rule evaluation support method with rule evaluation models, which are obtained with objective ...

Today’s real world faces different kinds of complex optimization problems. The existing methodologies can’t cope of with such complex problems. This paper presents classification rule mining as a multi-objective problem rather than a single objective one. Multi-Objective optimization is a challenging area and focus for research. Here two modern domains of research are discussed one is swarm int...

Since its introduction in the mid-nineties, Dung’s theory of abstract argumentation frameworks has been influential in artificial intelligence. Dung viewed arguments as abstract entities with a binary defeat relation among them. This enabled extensive analysis of different (semantic) argument acceptance criteria. However, little attention was given to comparing such criteria in relation to the ...

Evaluating the performance of a data mining technique is a fundamental aspect of machine learning. Evaluation method is the yardstick to examine the efficiency and performance of any model. The evaluation is important for understanding the quality of the model or technique, for refining parameters in the iterative process of learning and for selecting the most acceptable model or technique from...