integrated neural network model
Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks
... artificial neural networks. The first model is based on feedforward multilayer perceptron, sANN, and the second one is the integrated neural network model, ...both neural ...
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KNOWLEDGE-BASED NEURAL NETWORK FOR LINE FLOW CONTINGENCY SELECTION AND RANKING
... Artificial Neural Network based method for MW security assessment corresponding to line outage events have been reported by various authors in the ...of Neural Networks is to extract rules that can ...
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Neural Network Based Model Predictive Control of Batch Extractive Distillation Process for Improving Purity of Acetone
... A dynamic optimization problem for the BED is transformed into a nonlinear programming (NLP) problem solved by a SQP-based optimization technique and the process models are integrated by the Gear’s type method. ...
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The development of a combined mathematical model to forecast the incidence of hepatitis E in Shanghai, China
... Autoregressive integrated moving average (ARIMA) has become one of the most popular and convenient linear models in time series fore- casting ...the model building process [15]. Although the ARIMA ...
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A combined machine learning algorithms and DEA method for measuring and predicting the efficiency of Chinese manufacturing listed companies
... DEA-CCR model combined with back-propagation neural network (BPNN-DEA), with genetic algorithm (GA) integrated with and back- propagation neural network (GANN-DEA), with support ...
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Non-linear water level forecasting of Dungun river using hybridization of backpropagation neural network and genetic algorithm
... Autoregressive Integrated Moving Average (ARIMA) or seasonal ARIMA (SARIMA), Backpropagation Neural Network (BPNN), Nonlinear Autoregressive Models with exogenous inputs (NARX), have been applied as ...
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A hybrid seasonal prediction model for tuberculosis incidence in China
... a model to predict TB epi- demics and to analyze its seasonality in ...autoregressive integrated mo- ving average class models (ARIMA) [11] and artificial neural network ...our model ...
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EXPERIMENTAL DESIGN OF CAPACITANCE REQUIRED FOR SELF EXCITED INDUCTION GENERATOR
... an integrated model of product quality forecasting system based on grey theory and neural ...grey neural network model with sparse input and output ...
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A Hybrid Intelligent Model for Software Cost Estimation
... intelligent model combining a neural network model integrated with fuzzy model (neuro-fuzzy model) has been used to improve the accuracy of estimating software ...proposed ...
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... artificial neural network models for predicting water levels at Kainji Dam, which supplies water to Nigeria’s largest hydropower generation ...five neural network models and an Autoregressive ...
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Construction Engineering Cost Evaluation Model and Application Based on RS-IPSO-BP Neural Network
... BP neural network are integrated to put forward a new model of construction engineering cost evaluation, namely, the model of construction engineering cost evaluation of optimized ...
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FORECAST PERFORMANCE OF UNIVARIATE TIME SERIES AND ARTIFICIAL NEURAL NETWORK MODELS
... better model for forecasting Nigeria monthly Precipitation time series data that exhibit seasonal, periodic variations and non-linearity is ...Autoregressive Integrated Moving Average (SARIMA), Fourier ...
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Neuro-Fuzzy Scheduler for the Control of Real Time Spherical Tank Process
... general neural- network model for fuzzy logic control and decision ...connectionist model combined the idea of fuzzy logic controller and neural network structure and learning ...
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ASSOCIATION RULE MINING BASED VIDEO CLASSIFIER WITH LATE ACCEPTANCE HILL CLIMBING APPROACH
... a neural network ensemble model to perform the judgement of combustion diagnosis based on the spectral distribution of the light intensity pulse signal of the ...single neural network, ...
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Knowledge-based Neural Network for Line Flow Contingency Selection and Ranking
... Artificial Neural Network (ANN) based method for MW security assessment corresponding to line outage events has been reported by various authors in the ...of Neural Networks is to extract rules that ...
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Human-level Moving Object Recognition from Traffic Video
... a neural network which is capable of simulating the mechanism of analyzing and learning of human ...learning network; the unsupervised learning is used for pre-training and training output of a lower ...
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A machine learning approach to voice separation in lute tablature
... learning model for voice separation in lute ...a model that learns from data: a neural network that predicts voice assignments for ...Markov model (HMM) ...the neural ...
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A Neural Network Approach for Numeral Font Recognition
... An SVM in its elementary form сan be used for binary сlassifiсation. It may, however, be extended to multi сlass problems using the one-against-the-rest approaсh or by using the one-against-one approaсh. Arora and ...
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Pattern recognition using multilayer neural-genetic algorithm
... with neural network to determine automatically the suitable network architecture and the set of parameters from a restricted region of ...multilayer neural-genetic algorithm was applied in ...
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Glyph aware Embedding of Chinese Characters
... It came to our late attention that independently, Liu et al. (2017) considered the same character- level modeling problem and experimented with vanilla CNN models almost identical to ours. They evaluated their method on ...
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