Back-propagation (bp)
Diagnosis of thyroid disorders using Back propagation method
... decisions propagation algorithm is ...where back-propagation algorithm is applied and trains the given thyroid ...disorders. Back propagation algorithm has been applied to many pattern ...
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A new levenberg marquardt based back propagation algorithm trained with cuckoo search
... on BP [9-10]. The BP learning has become the standard method and process in adjusting weights and biases for training an ANN in many domains ...Error Back Propagation (EBP) algorithm [12, 13] ...
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A new back propagation neural network optimized with cuckoo search algorithm
... In order to overcome the weaknesses of the conventional BP, this paper proposed a new meta-heuristic search algorithm, called cuckoo search back propagation (CSBP). Cuckoo search (CS) is developed by ...
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Classification Using Two Layer Neural Network Back Propagation Algorithm
... network back propagation algorithm. Back propagation algorithm is used to train the neural ...network back propagation al- ...
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A new Cuckoo Search Based Levenberg Marquardt (CSLM) algorithm
... and back propagation algorithm ...on back propagation [9-10]. The back-propagation (BP) learning has become the most stan- dard method and process in adjusting weight and ...
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A Robust Intrusion Detection System by Utilizing Support Vector Machine and Error Back Propagation Neural Network
... Abstract: The concept of Intrusion Detection System is used in the work. The data set is used for training and testing. Various numeric features of dataset are selected for better accuracy.SVM that is Support Vector ...
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Back – Propagation Control Algorithm for Power Quality Improvement using DSTATCOM
... a back-propagation (BP) algorithm is implemented in 3-phase shunt connected custom power device known as DSTATCOM for extraction of the weighted value of the load reactive power and active power ...
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An Efficient and Robust Fall Detection System Using Wireless Gait Analysis Sensor with Artificial Neural Network (ANN) and Support Vector Machine (SVM) Algorithms
... classifier, back propagation was applied according to Duda et ...standard BP ANN ...the back propagation learning algorithm [8] is the repeated application of the chain rule to ...
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Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification
... and back propagation Elman recurrent network (BPERN) in achieving fast convergence rate and to avoid local minima ...using BP algorithm and other hybrid variants ...
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Artificial Intelligence in the Estimation of Patch Dimensions of Rectangular Microstrip Antennas
... of back propagation training algorithm of MLFFBP-ANN (Multilayer feed forward back propagation Artificial Neural Network) and RBF-ANN (Radial basis function Artificial Neural Network) has been ...
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Power Quality Improvement by Back Propagation Control Algorithm Using DSTATCOM
... A BP based control algorithm is used for extraction of fundamental weighted value of active and reactive power components of load ...currents. Back propagation algorithm which is trained the sample ...
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A review on Compressing Image Using Neural Network techniques
... the back propagation neural network and also combining the Levenberg-Marquardt concept with ...the back propagation neural network showed that compression of image and convergence time can be ...
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Bat BP: a new bat based back propagation algorithm for efficient data classification
... particularly back propagation algorithm is a complex task of great importance in the field of supervised ...with back-propagation neural network (BPNN) algorithm in-order to gain optimal ...
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STUDIES ON IMPROVING TEXTURE SEGMENTATION PERFORMANCE USING GENERALIZED GAUSSIAN MIXTURE MODEL INTEGRATING DCT AND LBP
... 3.1. Neural Network using Back Propagation A BPNN learns by utilizing the generalized delta rule in a two phase propagate- adapt cycle. The first randomly drawn weights are applied to the NN in order to ...
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Optimizing Back Propagation using PSO Hill A* and Genetic Algorithm
... algorithm[13]. BP algorithm has solved a number of practical problems, but it easily gets trapped in local minima especially for complex function approximation problem, so that back propagation may ...
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Artificial Neural Network Based Method for Location and Classification of Faults on a Transmission Lines
... repairing of these faults are critical in maintaining a reliable power system operation [2]. When a fault occurs on a transmission line, the voltage at the point of fault suddenly reduces to a low value. Fault location ...
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Determination of Corrosion Types from Electrochemical Noise by Artificial Neural Networks
... In this paper, a novel approach for distinguishing the type of corrosion from Electrochemical Noise (EN) signals is presented. A database containing numerous sets of original EN data is established， then the database is ...
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Optimizing Back-Propagation using PSO_Hill and PSO_A*
... Pillai , K. G. [1] explains a novel overlapping swarm intelligence algorithm is introduced to train the weights of an artificial neural network. Training a neural network is a difficult task that requires an effective ...
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Power Load Forecasting using Back Propagation Algorithm
... 4.4. BACK-PROPAGATION ALGORITHM (BPA) Newton‟s Steepest descent rule is used in the learning to achieve the global minimum. The flowchart illustrated in Figure 5 depicts the BPA. Training the ANN, involves ...
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Lower back pain: a need for thorough assessment
... In musculoskeletal care, the problem list helps the practitioner decide whether it is appropriate to treat the patient and if not, where best to send the patient for further assessment or treatment. Cohen et al (2008) ...
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