Water quality experiments are difficult, costly, and time-consuming. Therefore, different modeling methods can be used as an alternative for these experiments. To achieve the research objective, geospatial artificial intelligence approaches such self-organizing map (SOM), neural network (ANN), co-active neuro-fuzzy inference system (CANFIS) were to simulate groundwater in Mazandaran plain north...

The Neural Networks are best at identifying patterns or trends in data and they are well suited for predicting or forecasting. Hence neural networks are extensively applied to biomedical systems. An analysis is carried out to motivate neural network applications in medical diagnosis. A special note is made on neural network effort on cancer diagnosis. This paper focuses on the importance of app...

The main aim of this study is proposing an assessment model for evaluating the supply chain sustainability across the automotive sector. In this study, through reviewing the sustainability indicators in the economic, social, environmental, and governance pillars, the fuzzy Delphi is applied. Then, survey method is used to implement the model designed in CANFIS to evaluate the sustainability ind...

abstract from longley, the various equations for determining the runoff to water management are presented by the researchers that are widely used in hydrologic sciences. in this study by using observational data, was evaluated empirical, artificial neural network (ann) and ca-active neuro-fuzzy inference system (canfis) models in estimation of runoff. for this purpose, by using climatic and phy...

In this communication, we propose the use of Support Vector Machines (SVM) for crop classification using hyperspectral images. SVM are benchmarked to well–known neural networks such as multilayer perceptrons (MLP), Radial Basis Functions (RBF) and Co-Active Neural Fuzzy Inference Systems (CANFIS). Models are analyzed in terms of efficiency and robustness, which is tested according to their suit...