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The use of wireless sensor networks (WSN) in tracking applications is growing at a fast pace. In these applications, the sensor nodes discover, monitor and track an event or target object. Wireless sensor networks are by nature harsh, uncertain and dynamic, therefore there are many noise sources which malignantly impact on the performance and the efficiency of a wireless sensor network. On the other...
In today's competitive markets for a business success it is essential to fully understand customers, to strive to maximally satisfy their desires and preferences, and on this basis build a solid, long-term and fruitful relationship with customers. This is the core of customer relationship management. Good customer understanding is the basis for increase of customer lifetime value, which encompasses...
Feed-forward artificial neural network are applied to establish network model and carry out training and testing and make predictions on coagulant dosage of a certain water plant in North China, which has achieved sound prediction effect.
Attracting more students into science and engineering disciplines concerned many researchers for decades. Literature used traditional statistical methods and qualitative techniques to identify factors that affect student retention up most and predict their persistence. In this paper we developed two neural network models using a feed-forward backpropagation network to predict retention for students...
This paper presents a new procedure for identification of multiple cracks in beam. Natural frequency is frequently used as a parameter for detection of cracks in the structures. The process of crack identification in presented procedure is consists of four stages. In first stage, three natural frequencies of a cantilever beam for different locations and depths of cracks were obtained using Finite...
Artificial Neural networks are utilized to predict flow properties of a confined, isothermal, and swirling flowfield in an axisymmetric sudden expansion combustor using a two-component laser Doppler velocimetry capable of measuring the mean velocity components and their statistics. Generalized feedforward, radial basis function, and coactive neuro-fuzzy inference system neural networks are tested...
Parameter identification is critical for modern control strategies in electrical power systems which is considered both dynamic performance and energy efficiency. This paper presents a novel application of ANN observers in estimating and tracking Salient-Pole Synchronous Generator Dynamic Parameters using time-domain, on-line disturbance measurements. The data for training ANN Observers are obtained...
High performance biometrics helps in reliably identifying persons for access authorization and other purposes. Iris recognition is very effective in identifying persons due to the iris' unique features and the protection of the iris from the environment and aging. We focus on the design and training of a feed-forward artificial neural network for high-performance iris recognition and investigate the...
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 implement an online training of dynamic neural networks (NNs) for identification and control of permanent magnet synchronous motor (PMSM) servo system. Utilizing two multilayer feed-forward NNs, it makes no such assumptions. The two networks work in tandem to simultaneously achieve system identification and adaptive control. The proposed control system is designed and its effectiveness...
Knowledge manufacturing system has the ability of modifying dynamically manufacturing mode rapidly when production environment factors change. It is essential to evaluate the matching degree of established manufacturing mode and changed production environment factors. In this paper, a matching decision model for self-adaptability of knowledge manufacturing system based on the fuzzy neural network...
The feedforward neural networks trained with the online backpropagation (BP) learning algorithm have been widely studied in various areas of scientific research and engineering applications. In this paper we further study the convergence property of the online BP learning algorithm. Unlike the existing convergence analysis mainly focusing on the convergence of the gradient sequence of the error functions,...
This paper investigates the use of neural networks to detect and locate early breast cancer using a simple feed-forward back-propagation neural network. In order to test the proposed algorithm, an electromagnetic simulator is used to build a three-dimensional breast model. Spherical tumors of radii 1 mm, 2 mm, 4 mm, and 5 mm are assumed to be at different locations in the breast model. An ultra-wideband...
Handwriting recognition has been one of the active and challenging research areas in the field of image processing and pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. In this paper an attempt is made to recognize handwritten characters for English alphabets without feature extraction...
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...
In this paper, we have developed a feedforward neural networks to detect and to diagnosis rotor fault on induction motors using stator currents. In the first step, causes and effects of rotor fault have been studied, particularly, the number of broken bars has been considered. Then, in the second step, the number of broken rotor bars has been localized by Artificial Neural Networks (ANN), using the...
The authors have published earlier a novel technique for the supervised training of feed-forward artificial neural networks using the Harmony Search algorithm. This paper proposes a parallel and distributed implementation method to speedup the execution time to address the training of larger pattern-classification benchmarking problems. The proposed method is a hybrid technique that adopts form the...
Handoff management is a key element in mobile networks to sustain an ongoing session of a user. In this paper, we propose a handoff management technique to reduce handoff delay and call dropping. This handoff management technique incorporates a prediction component which will predict a UE's next cell and best handoff time. The prediction component is realized using a predictive model which uses earlier...
The paper justifies the necessity to use the hand writer identification using the feed forward neural networks. Identifying the authors of a handwritten sample using automatic image-based processing methods is an interesting pattern recognition problem with direct applicability in the legal and historic documents. Leading a worrisome life among the harder forms of biometrics, the identification of...
Titanium alloy exhibits an excellent combination of bio-compatibility, corrosion resistance, strength and toughness. The microstructure of an alloy influences the properties. The microstructures depend mainly on alloying elements, method of production, mechanical, and thermal treatments. The relationships between these variables and final properties of the alloy are complex, non-linear in nature,...
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