[PDF] Top 20 An Effective Artificial Neural Network based Power Load Prediction Algorithm
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An Effective Artificial Neural Network based Power Load Prediction Algorithm
... Genetic Algorithm (GA) is a heuristic search technique which is widely used to find the optimal ...the neural network ...genetic algorithm with the combination of some other such as Particle ... See full document
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Electrical Load Forecasting in Power Distribution Network by Using Artificial Neural Network
... electrical power markets and distribution network is supplying the customer ...electrical power in distribution network. The pattern of electrical power usage depends on many different ... See full document
7
Reliability Prediction of Power Communication Network Based on BP Neural Network Optimized by Genetic Algorithm
... is based on the business in the business model, and each service passes through one of the simplest physical links between the communication nodes A and B, that is, one of the two communication nodes (stations) ... See full document
6
Dynamic Monitoring and Optimization of Fault Diagnosis of Photo Voltaic Solar Power System Using ANN and Memetic Algorithm
... monitoring based on component level is a ...intelligent algorithm is also an ...use algorithm based on distributed on-line monitoring of photo voltaic array of XBee wireless sensor ... See full document
11
An Effective Intelligent Self Construction Multilayer Perceptron Neural Network
... new algorithm as an alternative approach for pattern classification of different statistical ...proposed algorithm can reach a consolidated structure size of artificial neural network ... See full document
6
Modeling of Power Consumption in Turning of Ferrous and Nonferrous Materials using Artificial Neural Network
... Artificial neural networks (ANN) have already been applied to various aspects of machining processes, such as optimization of machining parameters [5]-[6], prediction of cutting load [7]-[8], ... See full document
6
Comparative Study of Different Techniques for Heart Disease Prediction System
... and Effective Heart Attack Prediction System Using Data Mining and Artificial Neural Network ...attack prediction has been ...clustering algorithm, which will extract the ... See full document
10
Abnormal Data Screening Method of Thermal Power Based on BP Neural Network Algorithm
... electric power industry as a breakthrough to build carbon market, it is necessary to promote the use of carbon continuous emission monitoring system to improve the accuracy of carbon emissions ...emissions. ... See full document
7
Prediction of Wave Power Generation Using a Convolutional Neural Network with Multiple Inputs
... the power generation device, which needs to be efficient and ...approach based on the CNN is investigated to predict the power generation of a WEC system using a double-buoy ...conventional ... See full document
18
Prediction of Petroleum Price Using Back Propagation Artificial Neural Network Based on Chaotic Self-Adaptive Particle Swarm Algorithm
... From the graph, it can be concluded that the training effect of CSAPSO-BP ANN model is good, and the predicted value and actual value of the model are relatively good. By training the set of trained models, the ... See full document
6
Carbon Monoxide Prediction Using Artificial Neural Network And Imperialist Competitive Algorithm
... making based on the human expert knowledge and linguistic variables, one can combine the consequences of fuzzy inference system with the potencies of neural networks such as learning, adjustment, ... See full document
10
Artificial Neural Network Based Load Shedding Technique for Industrial System
... disturbance power as shown in Figure ...disturbance power, spinning reserve, droop, governor parameter settings ...The load shedding amount is calculated for all possible disturbances and in-plant ... See full document
9
Applying Fuzzy Logic Model for Bending Rigidity Evaluation of Woven Fabrics
... predictive power of each methodology was estimated by comparing the predicted fabric property values, obtained from mathematical, empirical and artificial neural network, with corresponding ... See full document
8
Artificial Neural Network Approach for Load Forecasting in Demand Side Management
... fluctuating load, utilities need to ensure sufficient transmission and generation resources to meet forecasted ...of power systems are greatly affected by load demand, significant savings can be ... See full document
6
Sla Aware Load Balancing Algorithm Using Join-Idle Queue for Virtual Machines in Cloud Computing
... decentralized load balancer) that is a load balancing architecture of decentralized ...(neural network based dynamic weighted round robin) that is a neural network ... See full document
7
Application of artificial bee colony algorithm to select architecture of a optimal neural network for the prediction of rolling force in hot strip rolling process
... a prediction method based on the Artificial Bee Colony algorithm and BP neural network, which was developed in order to improve the prediction of rolling force in hot ... See full document
8
Intelligent Control Algorithm for Maximum Power Point Tracking of PV Arrays
... system power available at the output of solar cell keeps on changing with changing irradiation, temperature and load because solar cell exhibits nonlinear V-I characteristic therefore MPP of solar cell ... See full document
10
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... Artificial neural networks controller has been investigated for automatic load frequency con- trol of a single area and two area power ...control algorithm is effective and ... See full document
8
Failure Prediction of Underground Pipeline Based on Artificial Neural Network
... A predictive model for underground pipeline is constructed with double parallel feed-forward neutral network. Neuron number in hidden layer and training function are investigated based on MATLAB. Through ... See full document
5
Prediction of prostate cancer by deep learning with multilayer artificial neural network
... Two to five hidden layers of ANN were composed of 5 neurons for each layer, the activation function of hidden layers was the ReLu function, loss function was cross entropy error function, back propagation ... See full document
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