[PDF] Top 20 A Neural Network Model to Solve DEA Problems
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A Neural Network Model to Solve DEA Problems
... a neural network to estimate the efficiency of DMUs (and inefficiency of DMUs) in large ...a neural network model as a solution tool in measuring the efficiency (and inefficiency) of ... See full document
7
Combining case-based reasoning with neural networks in diagnostic systems
... the neural network makes hypotheses and provides remindings for the CBR module in the selection of a previous case that can support one of the ...For problems where the neural network ... See full document
186
A neural network approach for machine breakdown repair time
... time, model change planning and perhaps helps the new product line up of certain ...breakdown problems and the need of breakdown’s repair time to be reduced for obtaining high machine utilization ... See full document
25
The evaluation of renewable energy power using hybrid model of neural network and data envelopment analysis (neuro - DEA)
... on DEA and Hybrid Model of Neural Network and Data Envelopment Analysis (Neuro- DEA) was ...combined model has higher ability. Therefore, where the basic model can't ... See full document
9
A study of Intrusion Detection System for Cloud Network Using FC-ANN Algorithm
... to solve the problem. Among these techniques Artificial Neural Network (ANN) is one of the widely used techniques and has been successful in solving many complex practical problems and ANN has ... See full document
6
Capturing User and Product Information for Document Level Sentiment Analysis with Deep Memory Network
... to solve the ...tional neural network for modeling sentences and Li et ...LSTM model that hi- erarchically builds an embedding for a paragraph from embeddings for sentences and ...LSTM ... See full document
6
OPTIMIZATION OF HIGH VOLTAGE POWER SUPPLY FOR INDUSTRIAL MICROWAVE GENERATORS FOR ONE MAGNETRON
... existing problems of 3D model retrieval based on neural network, this paper proposes a new algorithm based on ...3D model into six 2D images by six perspective ... See full document
5
Advances in Theory of Neural Network and Its Application
... This neural network is trained using enough number of corresponding patterns until synaptical values ...The neural network called back propagation is an extended version of simple ...this ... See full document
8
A NOVEL LEADER ELECTION ALGORITHM FOR HONEYCOMB MESH NETWORKS
... serious problems such as recurrent readmissions of patients, increase the mortalities, and very little time window left for the clinician to take prompt medical action to treat the patient upon the ...Artificial ... See full document
10
Neural Network Design - Free Computer, Programming, Mathematics, Technical Books, Lecture Notes and Tutorials
... of neural networks in literature re- search by Aston ...“the network can be taught to recognize individual writing styles, and the researchers used it to compare works attributed to Shakespeare and his ... See full document
1012
Fire Detection Using Cnn Approach
... color model, moving pixel detection and analyzing shape of fire colored pixels in ...colour model is used to detect information related to colour and ...the model was reduced from 238 MB to 3 MB, ... See full document
5
Comparative Study of Static and Dynamic Artificial Neural Network Models in Forecasting of Tehran Stock Exchange
... artificial neural networks has many considerable advantages; first, neural networks have a high similarity with the human nervous system, and unlike the traditional methods, they are data-driven ... See full document
17
A Study on Effective Algorithm for Medical Decision Making System
... metaphors: Neural Networks, Fuzzy Logic and Genetic Algorithms in a hybrid ...The Neural Networks and Fuzzy Logic metaphors are coupled in one system called Fuzzy Neural ...Fuzzy Neural ... See full document
9
BAT ALGORITHM FOR ROUGH SET ATTRIBUTE REDUCTION
... builds model after few sample data accumulating, which can weaken the randomness of the original data, find the data conversion rule, and finally realize forecast ...this model. Neural network ... See full document
5
Extreme Learning Machine Weight Optimization using Particle Swarm Optimization to Identify Sugar Cane Disease
... artificial neural network method with the Extreme Learning Machine (ELM) model can solve the problem of sugar cane disease classification with multilevel and multilabel symptom data with an ... See full document
10
A Comparison of Three Stage DEA and Artificial Neural Network on the Operational Efficiency of Semi Conductor Firms in Taiwan
... forward model used for forecasting ...the network to minimize the mean squared error (MSE) which measures the difference be- tween the real and the desired values over all output neurons and all learning ... See full document
12
Learning to Solve NP-Complete Problems: A Graph Neural Network for Decision TSP
... The reproducibility of machine learning studies and experi- ments is relevant to the field of AI given the myriad of param- eters and implementation decisions one has to make. With this in mind, we summarize here the ... See full document
8
Prediction of Petroleum Price Using Back Propagation Artificial Neural Network Based on Chaotic Self-Adaptive Particle Swarm Algorithm
... specific problems of the oil price forecast, set up the network input node is 7, representing the 7 price impact index, namely OPEC crude oil supply, Chinese crude consumption, OECD petroleum supply, ... See full document
6
Using MOLP based procedures to solve DEA problems
... Additive model and the E-K formulation in MOLP and show how a DEA problem can be solved interactively without any prior judgment by transforming it into an MOLP ...in DEA can be ...basic DEA ... See full document
15
Neural Network in Data Mining
... can solve simple problems like linear problem with one decision ...non-linear problems, we can join two or more single layer perceptrons known as multilayer ...complex problems, in two layer ... See full document
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