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In this paper, a Neural Network Deployment (NND) algorithm is presented to realize and synthesize Multi-Valued Logic (MVL) functions. The algorithm is combined with back-propagation learning capability and MVL operators. The operators are used to synthesize the functions. Consequently the synthesized expressions are applied by the MVL neural operators. The advantages of NND-MVL algorithm are demonstrated...
In the area of image processing and Optical Character Recognition, Segmentation is one of the steps which plays an important role in dealing with offline and online text images. Character segmentation means breaking an image with word into a sequence of characters. A broad perspective of segmentation lies in segmenting the characters in CAPTCHA (Completely Automated Public Turing Tests to Tell Computers...
This paper proposes an intellectual classification system to recognize normal and abnormal MRI brain images. Nowadays, decision and treatment of brain tumors is based on symptoms and radiological appearance. Magnetic resonance imaging (MRI) is a most important controlled tool for the anatomical judgment of tumors in brain. In the present investigation, various techniques were used for the classification...
Epilepsy is a global problem, and with seizures eluding even the smartest of diagnosis, a requirement for automatic detection of the same using electroencephalogram (EEG) would have a huge impact in diagnosis of the disorder. Contemporary researchers went ahead and devised a multitude of methods for automatic epilepsy detection, becoming a reason why one should find the best method out, based on accuracy,...
Polyneuropathy (PNP) and aging both bring changes to the walking pattern of elderly people. However, the identification methods of PNP from gait patterns were not sufficiently investigated from a technical perspective. In this study an automated classification method was developed to discriminate the neuropathic gait from both young healthy and old healthy gait using artificial neural network (ANN)...
In the foreign currency exchange (FOREX), a technical data analysis system for predicting currency movements is needed to help traders in decision making. Thus, this study proposes a system of technical data analysis to movement prediction of Euro to USD using Genetic Algorithm-Neural Network (GANN). To generate a predicted value, Genetic Algorithm searching for the best value of Feed Forward Neural...
Thyroid gland is one of the endocrine glands in the human body which produces thyroid hormone. This gland actively produces two kinds of hormone, namely thyroxine (T4) and triiodothyronine (T3). These hormones aim to produce protein, govern body metabolism, as well as to control body temperature circulation. Either excess or lack of these hormones will disturb those activities. The condition of excessive...
This paper proposes a short-term energy price classification model using decision tree. The proposed model does not predict the exact value of future electricity price, but the class to which it belongs, established with respect to pre-specified threshold. This strategy is proposed since for some applications, the exact value of future prices is not required for the decision-making process. A feature...
This paper investigates the accuracy of predictive auto-scaling systems in the Infrastructure as a Service (IaaS) layer of cloud computing. The hypothesis in this research is that prediction accuracy of auto-scaling systems can be increased by choosing an appropriate time-series prediction algorithm based on the performance pattern over time. To prove this hypothesis, an experiment has been conducted...
Today in data mining research we are daily confronted with large amount of data. Most of the time, these data contain redundant and irrelevant data that it is important to extract before a learning task in order to get good accuracy. The fact that today's computers are more powerful does not solves the problems of this ever-growing data. It is therefore crucial to find techniques which allow handling...
In power electronic systems, capacitor is one of the reliability critical components. Recently, the condition monitoring of capacitors to estimate their health status have been attracted by the academic research. Industry applications require more reliable power electronics products with preventive maintenances. However, the existing capacitor condition monitoring methods suffer from either increased...
Human activity recognition (HAR) is the basis for many real world applications concerning health care, sports and gaming industry. Different methodological perspectives have been proposed to perform HAR. One appealing methodology is to take an advantage of data that are collected from inertial sensors which are embedded in the individual's smartphone. These data contain rich amount of information...
Facial expressions are most commonly used for interpretation of human emotion. Over the last few decades, major advances in understanding and analysis of facial expression was achieved by application of computer vision, image processing, and machine learning techniques. In this paper we propose a method to classify facial expression in two classes using the Zernike moments. The proposed system consists...
In this work, an effort has been made to identify vocal and non-vocal regions from a given song using signal processing techniques and machine learning algorithm. Initially spectral features like mel-frequency cepstral coefficients (MFCCs) are used to develop the baseline system. Statistical values of pitch, jitter and shimmer are considered to improve performance of the system. Artificial neural...
In recent years, Artificial intelligence based algorithms are being widely used as prediction models in different domains. However, the suitability and performance of a particular technique depends on the essence of the prediction problem at hand. In this paper we perform a comparison of prediction performance of two widely used AI techniques namely Adaptive Neuro-fuzzy inference system (ANFIS) and...
The current development of electric power systems brings about the need to deal with increasingly multifaceted interactions of various technical components and relevant actors in order to integrate more comprehensive spectrum of different aspects into a single system. Thus, here is a proposed system of an intelligent control system using multi perceptron method of supervised learning, where the system...
Remote Sensing is widely used for mapping of land cover and land use. Classification of image satellites is also done by using these mapping. In this paper the classifier proposed is the Probabilistic based Neural Network developed using MATLAB. The data for image classification is acquired over various parts of Mumbai region which is LISS-III. Probabilistic based neural network is a supervised classification...
We present a new method for shot boundaries detection and classification that operates directly on the MPEG compressed video. It is based only on the information about the macroblock coding mode in P and B frames. In order to maintain good accuracy while limiting complexity, the system follows a two-pass scheme and has a hybrid rule-based/neural structure. A rough scan over the P frames locates the...
Detecting and diagnosing the liver focal lesions have vital importance in planning the treatments of the patients. While there is no need to apply any treatment for benign lesions, medical treatments or surgical operations are necessary in case of existence of malign lesions. Pre-contrast, arterial, portal venous and delayed venous phases in magnetic resonance imaging help to make clear diagnosis...
Rainfall and river flow are one of the most difficult elements of hydrological cycle to predict. This is due to tremendous range of variability it displays over a wide range of scale both in terms of space and time. The situation is further aggravated by the fact that rainfall-runoff is also very difficult to measure at scales of interest to hydrology and climatologic. Computational intelligence techniques...
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