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Fundamentals of neural networks
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The article was published on 1993-01-01 and is currently open access. It has received 1921 citations till now. The article focuses on the topics: Time delay neural network & Physical neural network.read more
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Making Sense of Data: A Practical Guide to Exploratory Data Analysis and Data Mining, Glenn J. Myatt
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Penerapan Learning Vector Quantization (LVQ) untuk Klasifikasi Status Gizi Anak
TL;DR: In this paper, a learning vector quantization (LVQ3) algorithm was used for children nutrient status classification, using of window parameter ( e ) in neural network LVQ3 effect positive impact.
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Real-Time Classification Algorithm for Recognition of Machine Operating Modes by Use of Self-Organizing Maps
TL;DR: Simulation results and extensive analysis, based on experimental data from a hydraulic excavator have shown that the proposed algorithm outperforms the standard one-model approach in terms of computation time for training and leads to a higher percentage of true recognitions.
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Available transfer capability (ATC) determination using intelligent techniques
TL;DR: In this paper ATC has been computed for real time applications using three different intelligent techniques viz., i) back propagation algorithm (BPA) ii) radial basis function (RBF) neural network and iii) adaptive neuro fuzzy inference system (ANFIS).
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Forecasting volatility in oil prices with a class of nonlinear volatility models: smooth transition RBF and MLP neural networks augmented GARCH approach
TL;DR: In this article, the forecasting capabilities of a new class of nonlinear econometric models, namely, the LSTAR-LST-GARCH-RBF and MLP models are evaluated.