Research Article of Research Journal of Mathematics and Computer Science
Expert System Model for Diagnosing Legume Diseases
Rahmon,I.A,Adebola_Akinsanya and Eze M.,.
Computer Science Department Babcock University, Ilishan, Ogun State.
There is a current surge in designing expert systems to solve problems like humans in different domains of research but there presently exist dearth of models that can guide designers of expert systems that can be used to accurately diagnose Soya beans diseases. Soya bean is a leguminous plant that is commonly grown in sub Saharan region and it is currently one of the legumes with high Gross Domestic Product (GDP) in the Nigerian economy, but farmers of this product are faced with serious challenges from legume ravaging diseases that are usually similar in symptoms and very difficult to diagnose by the few practising botanist available. Most models available cannot be used to guide designers who are interested in developing secured and reliable expert systems that can accurately classify, identify, diagnose and recommend treatments for Soya beans diseases. The main aim of this paper is to review existing models that are currently being used in designing expert systems and identify their limitations in other to come up with a better, more reliable and secured model. In other to identify inherent gaps from other models, research review method was adopted to critically investigate the weak points in few related and current expert models for classifying and diagnosing legumes diseases.
Keywords: expert system model, diagnosing legume diseases
How to cite this article:
Kasali et al., A Conceptual Design and Evaluation Framework for Mobile Persuasive Health Technologies (Usability Approach). Research Journal of Mathematics and Computer Science, 2017; 1:4.DOI:10.28933/rjmcs-2017-10-1403
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