Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...

Deep learning is one of the subsets of machine learning that is widely used in Artificial Intelligence (AI) field such as natural language processing and machine vision. The learning algorithms require optimization in multiple aspects. Generally, model-based inferences need to solve an optimized problem. In deep learning, the most important problem that can be solved by optimization is neural n...

Medical diagnosis and decision making is rather an empirical than a statistical process. Improvements in artificial intelligence methods (Neural networks, fuzzy systems, genetic algorithms) have opened a new way for developing MedicalDecision-Support-Systems. As there is no established communication platform in this specialized research field, the authors designed a “virtual-text-book“ for inte...

one of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of an image where the preciseness and reliability of its results will affect directly on the comprehension machine system made objective world. several edge detectors have been developed in the past decades, although no single edge detector...

electricity price predictions have become a major discussion on competitive market under deregulated power system. but, the exclusive characteristics of electricity price such as non-linearity, non-stationary and time-varying volatility structure present several challenges for this task. in this paper, a new forecast strategy based on the iterative neural network is proposed for day-ahead price...

Improving phoneme recognition has attracted the attention of many researchers due to its applications in various fields of speech processing. Recent research achievements show that using deep neural network (DNN) in speech recognition systems significantly improves the performance of these systems. There are two phases in DNN-based phoneme recognition systems including training and testing. Mos...

background: we aimed to assess the high-risk group for suicide using different classification methods includinglogistic regression (lr), decision tree (dt), artificial neural network (ann), and support vector machine (svm). methods: we used the dataset of a study conducted to predict risk factors of completed suicide in hamadan province, the west of iran, in 2010. to evaluate the high-risk grou...

In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Unce...