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The relevance of this study is stipulated by the necessity of designing algorithms allowing to improve the efficiency of human face detection and emotions recognition on images with complex background. Purpose: Development of algorithms and software system allowing to improve the efficiency of human face detection and in addition facial expression classification on images with complex background,...
Prediction in the stock market is challenging and complicated for investors. Many researches have performed to sense the future market movements. In the stock market, social media data have high impact today than ever. In this work, various prediction algorithms are analyzed to build a prediction model. The prediction model will be based on monthly prediction and daily prediction to forecast the next...
Artificial Neural Networks (ANNs) are human made information processing artifacts, and grown up vast in two-three decade. Neural Networks are highly parallelized dynamic system which accept output response as input and produce output. They have confirmed to be extensively beneficial in solving those problems which cannot be solved by using algorithmic procedures which are considered to be conventional,...
This paper discusses the development and application of a decomposition neural network rule extraction algorithm for nonlinear regression problems, the algorithm is called the piece-wise linear artificial neural network or PWL-ANN algorithm. Rules in the form of linear equations are generated by approximating the sigmoid activation functions of the hidden neurons in an artificial neural network (ANN)...
Machine learning (ML) based applications that require data stream processing have become quite common over the past few years. To deal with continuous and massive streams of data, low computational and memory costs are required from the ML techniques employed; these requirements can be partially fulfilled by using constructive neural networks (CoNN) algorithms. The automatic definition of the Neural...
For industrial applications, Bidirectional DC-DC converters (BDCs) are used in recent years. And also their efficiency results are improved to apply different control methods. ANN algorithms is one of the new control topic in literature. This paper attempts to improve the dynamic performance of bidirectional dc-dc converter. And it deals with a novel control scheme related with an adaptive input voltage...
Feature selection is an increasingly important part of machine learning. The purpose of feature selection is dimension reduction in a large multi-dimensional data set and it can be the key step of successful knowledge discovery in those problems where the number of features is large. This research area has huge practical significance because it accelerates decisions and improves performance. The requirements...
The relevance of this study is stipulated by the necessity of designing algorithms allowing to improve the efficiency of characters recognition on images with complex backgrounds subjected to noise, affine and projective transformations. Purpose: Development of algorithms and software system allowing to improve the efficiency of characters recognition on images with complex backgrounds subjected to...
Power transmission is one of the fields drastically growing in the world presently. In this paper, it is aimed to provide a solution for detecting the fault and its location accurately by utilizing ISFHA-[Improved Sheep Flock Heredity Algorithm]. It is necessary to satisfy the customer in terms of power quality transmission. Power quality damages occur due to short circuit, natural disasters and other...
Data mining applications are becoming a more common tool in understanding and solving educational and administrative problems in higher education. In general, research in educational mining focuses on modeling student’s performance instead of instructors’ performance. One of the common tools to evaluate instructors’ performance is the course evaluation questionnaire to evaluate based on students’...
Cardiac arrhythmia detection at the initial stage saves the patient from sudden death caused due to cardiac arrest. Arrhythmia can be predicted by detecting Ventricular Tachycardia and Ventricular Fibrillation. There are many techniques and methods for the detection of arrhythmia. The system proposes a highly efficient VF detector. It uses 18 parameters extracted from the ECG as input. These parameters...
The bag-of-words (BoW) model has been widely used for acoustic event classification (AEC). The performance of the BoW based AEC model is much influenced by "codebook construction" and "histogram generation". The common approaches for constructing the codebook and generating the histogram are the K-means and vector quantization encoding (VQE) respectively. However, they have some...
Smart Building (SB) exploits advances in information and communication technologies in order to provide the next generation of information and automation services that will significantly reduce operational costs and improve performance and efficiency. SB elements are typically interconnected using short range wireless communication technologies such as ZigBee, which is the most used wireless communication...
For today the unit neural networks are widely used to solve various problems. In this regard the issue of developing learning algorithm that would be able to optimize the structure of neural networks dynamically is very important. The existence of such a method would allow the researcher to get the structure of the neural network that would be best-answered domain and available input data quickly.
machine learning algorithms are widely used in classification problems. Certainly, recognition quality of algorithms is important indicator, but the ability of the algorithm to learn is more significant. In this work the learning curves experiment was performed in order to identify which of the three learning rates occur when training the machine learning algorithms: overfitting, perfect case and...
Extracting meaningful pattern from data can be challenging. Irrelevant, redundant, noisy and unreliable data, misinterpretation of results and incompatibility of a technique to extract unknown patterns from data may lead analyst to develop an erroneous classifier. This research is encouraged by ‘No Free Lunch’ theorem that can be simplified as no classification technique that works best for every...
Skin detection serves as a preliminary step for number of applications like face detection, gesture recognition, internet pornographic image filtering, and surveillance system. Number of artificial neural network (ANN) based skin detection algorithms have been presented in literature which are mostly based on back propagation (BP) ANNs. This paper attempts to analyze the performance of skin classifiers...
This paper describes our custom-designed wireless gait analysis sensor (WGAS) system developed and tested for real-time fall detection. The WGAS is capable of differentiating falls vs. Activities of Daily Living (ADL) and the Dynamic Gait Index (DGI) performed by young volunteers using a Back Propagation Artificial Neural Network (BP ANN) algorithm. The WGAS, which includes a tri-axial accelerometer,...
The present study reports the effect of showing horror movie clip on the autonomic nervous system (ANS) and the physiology of the conduction pathway of the heart of the volunteers. The volunteers were in the age group of 21–23 years of age and were of multi-ethnic culture. Horror clip was used to modulate the emotional states of the volunteers. The physiology of the ANS was studied non-invasively...
Looking for fast, automatic, less expensive and accurate method to detect plant diseases is of great realistic significance. By using the symptoms of the plant disease leaves, a supervised orthogonal nonlinear dimensionality reduction algorithm, named orthogonal locally discriminant projection (OLDP), is presented for plant disease recognition in this paper. The proposed algorithm aims to find a projecting...
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