this paper intends to offer a new iterative method based on articial neural networks for finding solution of a fuzzy equations system. our proposed fuzzied neural network is a ve-layer feedback neural network that corresponding connection weights to output layer are fuzzy numbers. this architecture of articial neural networks, can get a real input vector and calculates its corresponding fu...

Abstract Hybrid engines are becoming more and widespread. Electric energy instead is a valid help to reduce the environmental impact. In hybrid engines, number of components higher this results in decrease reliability. With Engine Health Monitoring (EHM) we mean set techniques used monitor health status system based on values assumed by some related parameters. Artificial Intelligence (AI) meth...

Typical computer-based parameter optimization and uncertainty quantification of the additive manufacturing process usually requires significant computational cost for performing high-fidelity heat transfer finite element (FE) models with different settings. This work develops a simple surrogate model using feedforward neural network (FFNN) fast accurate prediction temperature evolutions melting...

This study presents a machine learning (ML)/artificial intelligence (AI)-based perspective to reliably predict and enhance the treatment efficiency of landfill leachate by classical-Fenton (c-Fenton) photo-Fenton (p-Fenton) processes. experiment also sought lower costs evaluating impact using different numbers UV-c (254 nm) lamps during p-Fenton processes, as well develop sustainable process de...

The differential diagnosis of erythemato-squamous diseases is a difficult problem in dermatology. Artificial Neural Network (ANN) classifies the given samples when trained and nearly 98 % classification accuracy is achieved. Generalized Feed Forward Neural Network (FFNN) can solve the multivariable classification problem of determination of skin disease. ANN approach is studied to determine the...

Brain is well protected inside the hard and bony skull that hampers the study of its functions as well as makes the diagnosis of brain diseases more difficult and challenging. In this paper we perform review study on brain tumor detection from Magnetic Resonance Image (MRI). Stages for brain tumor detection using MR image are Pre-processing, Segmentation, Feature Extraction, Classification. The...

Feed forward neural networks (FFNN) with an unconstrained random number of hidden neurons deene exible non-parametric regression models. In M uller and Rios Insua (1998) we have argued that variable architecture models with random size hidden layer signiicantly reduce posterior mul-timodality typical for posterior distributions in neural network models. In this chapter we review the model propo...

Malignant lymphoma is one of the types malignant tumors that can lead to death. The diagnostic method for identifying a histopathological analysis tissue images. Because similar morphological characteristics types, it difficult doctors and specialists manually distinguish lymphomas. Therefore, deep automated learning techniques aim solve this problem help clinicians reconsider their decisions. ...

The Covid-19 pandemic has resulted in all activities having to be carried out by implementing physical distancing or social accordance with health protocols for mutual safety. government encourages people do more at home, including shopping. Consumer perception of purchasing goods online is a process evaluating various alternatives and choosing one alternative purchase using internet media. app...