MULTI-CRITERIA EVALUATION OF ARTIFICIAL NEURAL NETWORK APPLICATIONS USING TOPSIS

Artificial Neural Networks (ANNs) represent a category of machine learning models that draw inspiration from the arrangement and operation of the human brain.These models consist of interconnected units or neurons, which are grouped into layers.ANNs find extensive application in computer-related tasks, encompassing activities like identifying patterns, categorizing information, predicting outcomes, and beyond.Within the domain of artificial intelligence and machine learning, Artificial Neural Networks (ANNs) have surfaced as a crucial and transformative technology.Within this abstract, we delve into a range of computer applications utilizing Artificial Neural Networks (ANNs), with each application strategically designed to leverage the capabilities of neural networks for various objectives.The applications discussed include NeuroNetApp, DeepLearnPro, SmartANN Master, AIBrainWave, and CogniTech Learn.The accompanying table presents distinct metrics related to each application, namely "SI Plus," "SI Negative," and "Ci."Although the precise definitions of these metrics are not revealed, they presumably offer insights into the performance, effectiveness, or pertinent characteristics of the applications.The realm of artificial intelligence has undergone a profound shift due to the influence of Satyanarayana Ballamudi https://iaeme.com/