Genetic Algorithms, Fuzzy Logic, Neural Networks, Data Visualisation

A genetic algorithm is a search heuristic based on Charles Darwin's natural selection hypothesis. This algorithm mimics natural selection, in which the fittest individuals are chosen for reproduction in order to create the following generation's children. A genetic algorithm (GA) is a metaheuristic inspired by natural selection that belongs to the larger class of evolutionary algorithms in computer science and operations research (EA). Genetic algorithms rely on biologically inspired operators including mutation, crossover, and selection to develop high-quality solutions to optimization and search problems. Optimizing decision trees for greater performance, solving sudoku puzzles, and hyperparameter optimization are just a few examples of GA applications.

Fuzzy logic is a method of variable processing that allows for the processing of numerous possible truth values using the same variable. Fuzzy logic tries to answer problems using an open, imperfect spectrum of facts and heuristics that allows for a variety of accurate conclusions to be reached. Fuzzy logic is used to solve problems by taking into account all relevant data and making the best choice possible given the input.

A neural network is a network or circuit made up of biological neurons, or an artificial neural network made up of artificial neurons or nodes in the modern meaning. A neural network is either a biological neural network (made up of biological neurons) or an artificial neural network (made up of artificial neurons) that is used to solve artificial intelligence (AI) challenges. Artificial neural networks model the connections of biological neurons as weights between nodes. These artificial networks could be used for predictive modelling, adaptive control, and other applications that require a dataset to train. Networks can extract conclusions from a complicated and seemingly unconnected set of data, resulting in self-learning as a result of experience.

The graphical depiction of information and data is known as data visualization. Data visualization tools make it easy to examine and comprehend trends, outliers, and patterns in data by employing visual elements like charts, graphs, and maps. Data visualization tools and technologies are critical in the Big Data environment for analysing enormous volumes of data and making data-driven decisions.