The fuzzy logic theory is the branch of mathematics dealing with uncertainty in measurement of any quantity or any estimation. The concept of fuzzy logic is based on the use of membership functions. The construction of such functions depends upon the range of values based of some functions or operations. The defined rules set can give rise to the application procedure and also controls of membership function. The fuzzy application includes control system engineering, image processing, power engineering, industrial automation, robotics, consumer electronics and artificial intelligence.
Some eminent technology domains like artificial intelligence, machine learning expert systems, has experienced many different and versatile application with the solutions to solve many complex problems. The inference rules of the fuzzy logic have been effectively used to different industries namely the manufacturing for solving lot of problem. Some of the noteworthy companies working on principles of machine-learning concepts with fuzzy principles are found as Anti-lock brakes by Nissan, Auto engine by Honda, Elevator control by Mitsubishi Electric, Palmtop computer by Hitachi, Dishwasher by Matsushita etc.
The prime objective of the proposed book will be to include:
The simplistic structure of fuzzy logic enables us to apply the very concept to the fields other than AI and machine learning are evolutionary computing and many other interdisciplinary fields. The computer vision and machine Learning and evolutionary approach has been well be interpreted by the fuzzy techniques and rule sets. The decision rules and the control thereupon can be done by means of the fuzzy set. There are number of application areas which include the fuzzy system and its application in different manner.
The field like computer vision, image processing and other Meta heuristic approaches with evolutionary computing has become some common face research application. The fine tuning of the classifier model along with the optimization of model can be done by the principles of fuzzy theories. Some of the well-known examples of application of the fuzzy theory concepts are the scopes in management fields, stock market analysis, information retrieval, linguistics and behavioral science as well with good yield. The data mining and stock market data prediction are two important areas which find the major fuzzy application. The fuzzy machine learning model in the ensemble pattern serves the purpose of all sorts of classification and prediction jobs with high level of accuracy. The application of fuzzy theories has become much effective in maintaining the high-level accuracy. The fuzzy concept in the ensemble pattern serves for both the classification and prediction jobs. The continuous and consistent evolution in the field of fuzzy domain gives rise to all sorts of classification and prediction. The two variations like fuzzy type 2 and intuitionistic fuzzy logic has shown the promising accuracy with versatile approach of application. The shortcomings of the simple fuzzy model can easily be overcome by such variants of fuzzy logic .The book has been developed keeping in view about readers of different categories starting from the students to the professionals and researchers as well . The development of the book and its content layout will be done so meticulously proving the enough insights of the subjects to the readers so that the readers can easily pursue their research concept from the book. Overall the book serve as the purpose of repository of good amount of information and their technical presentations.
