A REVIEW STUDY ON SEQUENTIAL ESSENCE USING GENETIC ALGORITHM AND FUZZY LOGIC APPROACH IN STOCK MARKET BASED ON NEURAL NETWORK

Abstract

Since time is money, time optimization is the most important issue, so researchers develop a system to schedule in the best way by applying best solutions. Once you look at the production line of a factory or the number of classrooms and classrooms in a university, it can be seen that having a schedule in these places not only helps to regulate things, but it also helps to optimize the use of resources such as time and limitation. A significant financial topic that has drawn the interest of scientists for a long time is the stock return or stock market forecast. It is believed that historical history is publicly accessible in a manner indicative of potential stock returns. This statistics include economic factors such as interest and exchange rates, detailed details on manufacturing, such as factory output growth rates and market costs, and specific data from businesses, such as financial statement and dividend returns. Technical research shows a fresh, substantial knowledge of psychological variables that affect market markets in a proposal to predict future price and pattern. Technically speaking, it is a reflection of the psychology of mass that try to anticipate market fluctuations in the future on the basis that the psychology of the crowd shifts from hysteria, apprehension and pessimism, to trust, irrational confidence and avarice, on the other. This paper presents an application of Neural Network for stock market predictions and is very useful for predicting world stock markets.