File Name: design and development of expert systems and neural networks .zip
Expert System is an interactive and reliable computer-based decision-making system which uses both facts and heuristics to solve complex decision-making problems. It is considered at the highest level of human intelligence and expertise. The purpose of an expert system is to solve the most complex issues in a specific domain. The Expert System in AI can resolve many issues which generally would require a human expert. It is based on knowledge acquired from an expert. Artificial Intelligence and Expert Systems are capable of expressing and reasoning about some domain of knowledge. Expert systems were the predecessor of the current day artificial intelligence, deep learning and machine learning systems.
The history of artificial neural networks ANN began with Warren McCulloch and Walter Pitts  who created a computational model for neural networks based on algorithms called threshold logic. This model paved the way for research to split into two approaches. One approach focused on biological processes while the other focused on the application of neural networks to artificial intelligence. This work led to work on nerve networks and their link to finite automata. In the late s, D.
Expert systems ES are one of the prominent research domains of AI. The expert systems are the computer applications developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise. Knowledge is required to exhibit intelligence. The success of any ES majorly depends upon the collection of highly accurate and precise knowledge. The data is collection of facts.
Expert system , a computer program that uses artificial-intelligence methods to solve problems within a specialized domain that ordinarily requires human expertise. Dendral, as their expert system was later known, was designed to analyze chemical compounds. Expert systems now have commercial applications in fields as diverse as medical diagnosis , petroleum engineering , and financial investing. In order to accomplish feats of apparent intelligence, an expert system relies on two components: a knowledge base and an inference engine. An inference engine interprets and evaluates the facts in the knowledge base in order to provide an answer.
Expert Systems and Applied Artificial Intelligence.
DePold, H. October 1, Gas Turbines Power. October ; 4 : — Condition monitoring of engine gas generators plays an essential role in airline fleet management. Adaptive diagnostic systems are becoming available that interpret measured data, furnish diagnosis of problems, provide a prognosis of engine health for planning purposes, and rank engines for scheduled maintenance.
Show all documents PDF superior Development of a speech enhancement system using deep neural networks. Development of a speech enhancement system using deep neural networks In the last years, deep neural networks have become an important tool in speech technologies, yielding notable advances in the fields of speaker and speech recognition and speech synthesis. In this project a design is proposed for a deep neural network for speech enhancement , that is capable of reducing the level of noise in speech recordings taken in real world scenarios such as a public transportation or a cafeteria. The proposed design is intended to reduce the high requirements of computing power of other models that make up the state- of -the-art in audio processing with deep neural networks , as well as the complexity of their architectures.
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and store the outputs into the EMR systems [7,18]. Knowledge acquisition: before designing an expert system,. the experts must be identif.