Three-phase induction motors are widely used in different applications the industry due to their robustness, low cost, and reliability. Untimely identification correct diagnosis of incipient faults reduce cost improve maintenance management these machines. This paper explores a new method for robust classification rotor failures three-phase (MITs) connected directly electrical network, operatin...

The aim of the current research was to develop models predict severity accidents on rural roads in Tehran province, Iran. In this regard, using accident data from 2017 2020, machine learning algorithms, including multiple logistic regression, multilayer perceptron neural network (MLPNN), and radial basis function (RBFNN) models, as well statistical methods, Kolmogorov–Smirnov test, Friedman fac...

Electronic noses (E-Noses) are becoming popular for food and fruit quality assessment due to their robustness and repeated usability without fatigue, unlike human experts. An E-Nose equipped with classification algorithms and having open ended classification boundaries such as the k-nearest neighbor (k-NN), support vector machine (SVM), and multilayer perceptron neural network (MLPNN), are foun...

Classification of electrocardiogram (ECG) signals plays an important role in clinical diagnosis of heart disease. This paper proposes the design of an efficient system for classification of the normal beat (N), ventricular ectopic beat (V), supraventricular ectopic beat (S), fusion beat (F), and unknown beat (Q) using a mixture of features. In this paper, two different feature extraction method...

Sentiment analysis plays a big role in brand and product positioning, consumer attitude detection, market research and customer relationship management. Essential part of information-gathering for market research is to find the opinion of people about the product. With availability and popularity of like online review sites and personal blogs, more chances and challenges arise as people now can...

Vulnerability assessment in power systems is important so as to determine how vulnerable a power system in case of any unforeseen catastrophic events. This paper presents the application of Radial Basis Function Neural Network (RBFNN) for vulnerability assessment of power system incorporating a new proposed feature extraction method named as the Neural Network Weight Extraction (NNWE) for dimen...

With an uninterrupted power supply to the consumer, it is obligatory balance electricity generated by load. The effective planning of economic dispatch, reserve requirements, and quality provision for accurate consumer information concerning load needed. burden on system engineers eased forecasting essential ensure enhanced operation reliable provision. Fickle nature, atmospheric parameters inf...

An Artificial Neural Network (ANN) is designed to investigate its application for data assimilation. This procedure provides an appropriated initial condition to the atmosphere to weather forecasting. Data assimilation is a method to insert observational information into a physicalmathematical model. The goal here is the process for assimilating meteorological observations. The numerical experi...

The handwriting is one of the most familiar communication media. Pen based interface combined with automatic handwriting recognition offers a very easy and natural input method. The handwritten signal is on-line collected via a digitizing device, and it is classified as one pre-specified set of characters. The main techniques applied in our work include two fields of research. The first one con...

Inverse kinematics of robot manipulator is to determine the joint variables for a given Cartesian position and orientation of an end effector. There is no unique solution for the inverse kinematics thus necessitating application of appropriate predictive models from the soft computing domain. Although artificial neural network (ANN) can be gainfully used to yield the desired results but the gra...