Reviewing of different algorithms application with qualitative variables for the different financial indicators

Nowadays the Machine Learning and Soft Computing algorithms are being deployed in different fields of applications and economy is one of them especially applied for decision making systems. The variables with their probabilistic values of their presence will be treated not like quantitative values but as qualitative ones. These linguistic variables are too near to human thinking where Fuzzy logic with its membership functions and as well combined with the application of the Boolean logic laws, all of them make it possible to construct a very accurate decision-making system. Decision making systems constructed by applying Fuzzy logic and Boolean laws can comply with trades fluctuations where uncertainty is quite common, and the business financial state as well is very unpredictable. These linguistic variables will be nothing less but the financial indicators of the small to medium businesses, where those are represented with linguistic variables with a probability of their values and appearance, and the decision for setting different weights to these indicators will help to create accurate economic models. Financial state of the firms we analyze is a multi-variable system and its variables are not simple numeric values, but they can be thought like analogue ones and by being like this those can reflect better the markets trend. The linguistic variables with multiple states that are studied come from the financial reports of the businesses and will undergo to different methods application like the DuPont, LA, LC [5]–[7].