1.3. OBJECTIVE OF THE STUDY
1.3.1. GENERAL OBJECTIVE
The main objective of this study is to develop a knowledge based system for mango diseases diagnosis and treatment using rule based reasoning approach.
1.3.2 SPECIFIC OBJECTIVES
• To review related literatures on concept of knowledge based system and available algorithms and techniques that give deep understanding to conduct this research work.
• To acquire the necessary tacit and explicit knowledge required for developing knowledge base system
• To model and represent knowledge acquired from domain experts and codified sources.
• To build prototype knowledge based system for mango diseases diagnosis and treatment.
• To evaluate the performance of the prototype knowledge based system.
1.4. SCOPE OF THE STUDY
The scope of this study was developing prototype knowledge base system and evaluating its application for mango diseases diagnosis and treatment for agronomy experts and farmers found in Ethiopia. There are a number of different approaches for designing knowledge based system but this system only focuses on rule based approach. The focus area of this study was Ambo Plant Protection Research Center for the purpose of data collection. This study is limited to diagnosis and treat related to diseases and providing possible suggestions for symptoms for decision making in mango diseases diagnosis. There are different problems related to fruit crop production but including all diseases diagnosis and treatment issues influence the effectiveness of fruit crop production in Ethiopia. Due to this reason this study focused on Mango diseases.
The task involved in conducting this work includes literature review, problem identification, knowledge acquisition, modeling, representation and implementation or encoding. The prototype is consists of knowledge base, inference engine, user interface, explanation facility and rule based reasoning mechanism. Even though the prototype includes all these components this system has limitation in automatic updating of the knowledge base by the user when the new factors are introduced, that is due to time limitation the learning component of the knowledge base is not developed in this study.
Generally, the study is intended to develop rule based prototype system that diagnosis mango diseases and giving advisory services or treatment primarily for domain experts and then for any interested party capable of reading English language.
1.5. SIGNIFICANCE OF THE STUDY
The result of this thesis work is expected to contribute a lot to the development of knowledge based advisory expert system for mango diseases diagnosis and treatment and motivate further researches to be conducted in the area of agricultural expert system. Furthermore, it can also help to initiate advisory expert system researches in Ethiopian. The system that researcher has proposed can help farmers in critical times where access to an agricultural expert is not forthcoming due to the unavailability of agriculture extension worker in the area. The system is especially useful in the country and the rural areas where the ratio of extension workers to the farmers is a small number and where the access to such experts is not feasible.
The immediate beneficiaries of the study are primary agriculture workers and agriculture professionals or agronomist. Particularly, the prototype will have great significance to teach primary agriculture extension workers, general agronomy experts in order to have well understanding about mango diseases. As a result, those agriculture workers can use the system in diagnosing mango diseases on primary agriculture sectors where highly qualified mental professionals are unavailable. The developed prototype knowledge based system is used to give advising services for diagnosing mango diseases. The prototype knowledge based system is developed using the knowledge of multiple domain experts and documentary sources to be preserved for in case experts soon retire or unavailable. Therefore, it gives better advisory services where highly qualified agronomists are occupied or where they are not found.
Additionally, the prototype can be used for agriculture professionals as a guide. Even though those professionals are highly qualified persons, they may get difficulty of remembering all the critical symptoms and signs of diseases.
Identifying the right diseases and giving diagnosis and treatment is the difficult task in mango diagnoses. Since the prototype is already codified by using appropriate domain knowledge, it solves the problem of forgetting the important issues and concepts of the domain knowledge by remembering the facts and rules already feed.
1.6. METHODOLOGY OF THE STUDY
In order to achieve the objectives of the study and address the stated problems successfully, methods suitable for gathering information, knowledge acquisition, knowledge representation, KBS development tools selection and system evaluation are identified. Here under the detail is presented.
1.6.1. RESEARCH DESIGN
Dipanwita et al. 40 were used experimental research design to develop intelligent medical system for diagnosis of common disease by acquiring tacit and explicit knowledge from domain knowledge expert. The domain knowledge was acquired and then represented. The acquired and represented knowledge was inserted into the knowledge base. Based on the result of evaluation of inserted knowledge it changed again and again. In addition, during prototype development stages the sequence of the facts and rules were changes again and again until it fitted the best sequence. Moreover, the way to test and evaluate the performance of the prototype system by feeding the cases and records the result to compare it against with the decision made by domain experts in similar settings.
The process of acquiring knowledge from experts and building a knowledge base is called knowledge engineering. The process of developing computational knowledge based systems is called knowledge engineering. This process involves assessing the problem, developing a structure for the knowledge base and implementing actual knowledge into the knowledge base. Knowledge engineering and system engineering methodologies were used to develop the system. To accomplish the knowledge engineering task three main activities were done. These are knowledge acquisition/elicitation, knowledge verification & knowledge modeling and representation.