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Department:  Computer Science
AMOUNT:  20000
PAGES:  95 pages, abstract, chapter 1-5 , APENDIX A source code and APENDIX B output, well reserached and supervised
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1.1            Background to the Study

Decision making is a frequent problem in today‘s economic, business and industrial world. Usually this type of decision making constitutes an essential decision. For instance in medical diagnosis, assigning patients to any one of the groups (at risk, less risk, not at risk) is based on some medical observations and tests. Classification rules are used in banks to differentiate solvent firms from the companies which may end up in bankruptcy. Credit card companies employ classification methods to detect small percentage of credit cards that are being used fraudulently. Examples of other applications of group classification analysis include fault detection, machine failure and decision to launch investment in a new product.

All of these two-group classification decisions have significant economic and social consequences, as an error of assigning an object to the wrong group may lead to catastrophic results. Because of the importance of making the correct decision, researchers and practitioner are constantly looking for better decision making procedure.

Due to continuous advancement in industrial and commercial fields, the exchange of information and its associated uncertainty also increases which in-turn raises the complexityof decision making problem in the form of uncertainty, subjectivity and vagueness. Medical practitioners exhibit variation in decision making because of their approaches to deal with uncertainties and ambiguity in knowledge and information. The diagnostic decisions also depend upon experience, capability and observation of the practitioner.

As the complexity of system increases, it is not easy to follow a particular path of diagnosis without any mistake. Artificial Intelligence was born in 1956, stepped in many areas but not in human level machine intelligence. Now–a–days AI is used in many areas inhuman level machine intelligence and it is applied for decision making, diagnosis, pattern recognition and analysis of evidence (Crawford, 2016). Very important branch of artificial intelligence is known as Expert Systems.With the domain knowledge as background, the task of decision making is to get abest solution from the input information from the user using inference method. There arethree ways to make decision in complex environment, they are

       i.            Constructing a mathematical model.

     ii.            Looking for human expert‘s suggestion.

  iii.            Constructing an Expert System or controller.

Building a mathematical model is a good way. How

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