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Heart disease is a deadly disease that large population of people around the world suffers from. When considering death rates and large number of people who suffers from heart disease, it is revealed how important early diagnosis of heart disease. Traditional way of diagnosis is not sufficient for such an illness. Developing a medical diagnosis system based on machine learning for prediction of heart...
The Artificial Neural Network (ANN) is a branch of science in the field of artificial intelligence and is created from adapting the workings of the human brain. Backpropagation (BP) and Learning Vector Quantisation (LVQ) are two of many methods used to recognise patterns. Both are supervised training methods with different approaches. BP uses an error value to recognise patterns or images, while LVQ...
Artificial Neural Network (ANN) forms a useful tool in pattern recognition tasks. Collection of five, eight or more cards in a cards game are normally called poker hands. There are various poker variations, each with different poker hands ranking. In the present paper, an attempt is made to solve poker hand classification problem using different learning paradigms and architectures of artificial neural...
Age classification is a useful tool for creating an automatic system that can identify or verify and classify a person into an age group. In this paper a unique approach for classifying different aged people based on their forearm electromyography (EMG) signal, which has different characteristics from teenager to old is proposed. The Electromyography signal generates from the movement of brachioradialis...
Breast cancer is one of the leading causes of cancer deaths among women in developed countries including India. Mammography is currently the most effective method for detection of breast cancer. Early diagnosis of the breast cancer allows treatment which could lead to high survival rate. This paper presents breast cancer detection in digital mammography using Image Processing Techniques by Artificial...
In 2010, Global Status Report on NCD World Health Organization (WHO) reported that 60 percent of deaths in the world caused by the non-communicable diseases, and one of the non-communicable diseases that consumed a lot of attention was diabetes mellitus. Diabetes is a serious threat to the health development, because diabetes is a disease that caused most other diseases (complications), such as blindness,...
This paper deals with time series exponential smoothing and artificial neural network-based backpropagation methods in formulating a reservoir inflow forecasting model for Angat Dam in the Philippines. The predictive model is trained using dam daily average inflow observations inclusive of years 2003 to 2012, as recorded. Any real-time inflows forming a 5-consecutive-day vector could serve as input...
Because of the complex dynamic behavior of supercapacitor, its modeling must be based on parallel, distributed structures (each component has to represent a model of activity, distributed on many processing units), with learning capacity. For this purpose, the paper proposes a new feed forward artificial neural network structure with two hidden layers and with backpropagation training. The neural...
There has been wide range of expansion in hand gestures close in style, pattern, movement and feature as well as in meaning. From that aspect this following paper confabs an improved version of hand gesture recognition based on segmentation process and backpropagation algorithm through the analysis of myoelectric signals generates from the movement of brachioradialis muscle and antebrachial vein of...
The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified...
The ever increasing need for energy efficient systems has led to various ingenious ideas about energy management. A major offshoot of this search for energy efficient solutions is demand management in power systems. The goal of any demand management program is to control the demand for electric power among customers thereby creating load relief for electric utilities and improving system security...
The basic principle of Artificial Neural Networks and BP algorithm was introduced in this paper. The application of BP algorithm Artificial Neural Networks in fault diagnosis of 40TM liquid-gas hammer was studied. The superiority of BP algorithm Artificial Neural Networks in fault diagnosis was proved by the MATLAB simulation and the training. The causes of faults were determined by BP algorithm Artificial...
Today's advanced muscular sensing and processing technologies have made the acquisition of electromyography (EMG) signal which is valuable. EMG signal is the measurement of electrical potentials generated by muscle cells which is an indicator of muscle activity. Other than rehabilitation engineering and clinical applications, EMG signals can also be employed in the field of human computer interaction...
This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for...
This paper presents a procedure for allocating reactive power using artificial neural network (ANN). Artificial neural network is trained based on data from Y-bus matrix. Training and testing of this ANN network have been done with five bus test system. Back propagation learning has been utilized to train the ANN. A numerical example on allocating reactive power using a feed forward back propagation...
This paper takes a kind of ceramic glaze as an example, and builds an improved BP neural network model for optimizing the formulation on ceramic glaze. The improved BP neural network adopts Levenberg-Marquardt algorithms. The paper reviews how to build the ceramic formulation optimization model based on BP artificial neural network, including the establishment of neural network, the training, and...
The feasibility of automating the evaluation of stroke chronic patients' motor functions has been explored while analyzing their corresponding fMRI studies with statistical parametric analysis, statistical inference analysis and a nonlinear multivoxel pattern-analysis classifier based on a feed-forward backward-propagation neural network. After doing principal component analysis and independent component...
Power utilization has become a major issue in portable designs, since its battery storage is less compared to its usage. One of the popular techniques to solve this problem is to use Dynamic Power Management (DPM) at the system level. Dynamic power management is a technique used to save power when the system is idle. Earlier it was assumed that the prediction can be done only in long range dependent...
A GPU-accelerated OpenCL implementation of a back-propagation artificial neural network for the creation of QSAR models for drug discovery and virtual high-throughput screening is presented. A QSAR model for HSD achieved an enrichment of 5.9 and area under the curve of 0.83 on an independent data set which signifies sufficient predictive ability for virtual high-throughput screening efforts. The speed-up...
In this paper the feasibility of artificial neural network technology for air fine particles pollution prediction of main traffic route was discussed. The concentration data of PM2.5, PM5 and PM10 were measured in Zhongshan road, the main traffic route of Chongqing, China. Parameter Φ of emission capacity of motor vehicles was used as the independent variable of prediction model. RBF and BP neural...
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