An Expert System Shell for Strengthen the BSE Prediction and Knowledge Representation Using Backward Reasoning Approach

Author(s)	Mr. Sachin Kamley, Dr. Dinesh Kumar Sahu, Dr. Varsha Namdeo
Country	India
Abstract	The stock market is characterized by uncertainty, which makes it difficult to convey knowledge and make predictions. Another well-known method that facilitates quick problem-solving and thoughtful decision-making is the expert system. Over the past few decades, a variety of tools and methods have been created for expert system shells. These methods and tools have completely failed to illustrate information and draw conclusions in an efficient way, which is the foundation of an expert system. In this direction, the expert system's backward reasoning method to knowledge representation and stock market prediction is used. One of the Artificial Intelligence (AI) languages that is especially well-suited for expert system applications is LISP (List Processing). The application and testing of the backward reasoning approach to stock market problems is the primary emphasis of this research study. To accomplish this, we use the Common Lisp 3.0 editor.
Keywords	Stock Market, Artificial Intelligence, BSE, Expert System, Backward Reasoning, Common Lisp 3.0
Field	Computer Applications
Published In	Volume 6, Issue 5, September-October 2025
Published On	2025-10-23
DOI	https://doi.org/10.63363/aijfr.2025.v06i05.1668
Short DOI	https://doi.org/g97v6z

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