Artificial Neural Networks (ANN)
Fine-tuning artificial neural networks automatically
... Artificial Neural Networks (ANN) are currently a widely used technique to solve complex problems on a wide range of real applications. Such applications vary from financial predictions to control ...
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Combining Artificial Neural Networks and GIS Fundamentals for Coastal Erosion Prediction Modeling
... Artificial neural networks (ANN) or simply a neural network, is a set of independent neurons linked together in the same way as the synapses, neurons, and dendrites of ours ...a neural ...
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ESTIMATION OF PHYSICAL AND CHEMICAL SOIL PROPERTIES BY ARTIFICIAL NEURAL NETWORKS
... trained artificial neural networks acquired the necessary knowledge to estimate the results of the analyzed soil properties, regardless of its spatial ...
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REFERENCE EVAPOTRANSPIRATION FORECASTING BY ARTIFICIAL NEURAL NETWORKS
... (MLP), which is a traditional Artificial Neural Network. Numerous topologies and variations were tested between neurons in intermediate and outer layers until the most accurate were obtained. We separated ...
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Artificial neural networks (ANN): prediction of sensory measurements from instrumental data.
... of artificial neural networks (ANN) since they are computational techniques well adapted to non-linear data (CHEN, 1991; NUI et ...or artificial neurons, arranged in a parallel, highly ...
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Design of Circular Microstrip Antenna Using Artificial Neural Networks
... an artificial neural network (ANN) model has been developed for design of circular microstrip patch ...proposed neural model completely bypasses the repeated use of complex iterative process for ...
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Flood routing modelling with Artificial Neural Networks
... with artificial intel- ...of artificial neural networks and the high computation requirements concerning the application of so- phisticated physically based ...
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Artificial neural networks for compression of gray scale images: a benchmark
... Digital images compression is one of the many problems to which artificial neural networks (ANN) have been applied. Since there are many types of ANNs, it is important know their relative performance ...
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Spatial predictive mapping using artificial neural networks
... Artificial neural networks (ANN) allow a multivariate data analysis of complex problems. Their ability to learn from given examples without an explicit programming of problem solution allows a ...
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Fuzzy nonlinear regression using artificial neural networks
... Artificial Neural networks are massively parallel, distributed processing systems representing a computational technology built on the analogy to the human information processing ...system. ...
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Selection in sugarcane families with artificial neural networks
... Abstract – The objective of this study was to evaluate Artificial Neural Networks (ANN) applied in an selection process within sugarcane families. The best ANN model produced no mistake, but was able ...
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Prediction of Electrochemical Machining Process Parameters using Artificial Neural Networks
... Artificial neural networks (ANNs), as one of the most attractive branches in artificial intelligence, has the potential to handle problems such as modeling, estimating, prediction, ...
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The use of artificial neural networks (ANN) in food process engineering
... —Artificial neural networks (ANN) aim to solve problems of artificial intelligence, by building a system with links that simulate the human ...others. Neural networks have been ...
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VOICE RECOGNITION USING ARTIFICIAL NEURAL NETWORKS AND GAUSSIAN MIXTURE MODELS
... as artificial neural networks (ANN) has also been explored as a useful technology to assist in statistical speech recognition [13-17] due to its discriminative and adaptive learning ...
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Wavelet transform and artificial neural networks applied to voice disorders
... Artificial Neural Networks are one of the most classifiers known in the literature and; therefore, it was chosen to classify laryngeal diseases in this ...
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Estimating soybean yields with artificial neural networks
... ABSTRACT. The complexity of the statistical models used to estimate the productivity of many crops, including soybeans, restricts the use of this practice, but an alternative is the use of artificial neural ...
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Digital soil mapping using reference area and artificial neural networks
... using artificial neural networks (ANN) and environmental variables that express soil- landscape ...The neural network simulator used was the Java NNS with the learning algorithm "back ...
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FLORISTIC DIVERSITY AND EQUITABILITY IN FOREST FRAGMENTS USING ARTIFICIAL NEURAL NETWORKS
... using artificial neural networks (ANN). Feedforward networks were used and they were trained through a back propagation error ...the networks was the Multilayer Perceptron (MLP), to ...
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The Use of Artificial Neural Networks (ANN) in Food Process Engineering
... Abstract Artificial neural networks (ANN) aim to solve problems of artificial intelligence, by building a system with links that simulate the human ...others. Neural networks ...
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Artificial neural networks for adaptability and stability evaluation in alfalfa genotypes
... problem, artificial neural networks were used for genotypes classification in accordance with the methodology of Eberhart and Russell ...of neural networks. Thus, by the trained ...
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