[PDF] Top 20 Application of Artificial Neural Networks Model as Analytical Tool for Groundwater Salinity
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Application of Artificial Neural Networks Model as Analytical Tool for Groundwater Salinity
... These networks of neurons are called neural networks, or natural neural ...mathematical model of a natural neural ...Treelike networks of nerve fibers called dendrites are ... See full document
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Technical note: Application of artificial neural networks in groundwater table forecasting – a case study in a Singapore swamp forest
... in groundwater table ...predict groundwater table variations in subsurface- drained ...using groundwater recordings and other hydrometeorological data to simulate groundwater ta- ble ... See full document
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Comparative Study between Neural Network Model and Mathematical Models for Prediction of Glucose Concentration during Enzymatic Hydrolysis
... hydrolysis. Artificial Neural Networks (ANNs) are very effective in developing predictive models for processes involving complex reaction kinetics that would otherwise be difficult to be modeled by ... See full document
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Application of Artificial Neural Networks in Civil Engineering
... Artificial neural networks are computers whose architecture is modeled after the ...simplified model of a real neuron which fires (sends off a new signal) if it receives a sufficiently strong ... See full document
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Application of Artificial Neural Networks in Cold Rolling Process
... applicable tool in all of the scientific ...the application of (ANN) in predicting the internal mechanical properties of cold rolling ...(ANN) application to a hot strip mill to improve the model’s ... See full document
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Overview of Artificial Neural Networks Applications in Groundwater Studies
... Artificial Neural Networks (ANNs) are part of Artificial ...to model the complex behaviour of aquifers which by nature are anisotropic and ... See full document
6
Tool Life Prediction in Face Milling Machining of 7075 Al by Using Artificial Neural Networks (ANN) and Taguchi Design of Experiment (DOE)
... and tool life can be applied to help businesses gain a competitive ...using analytical tools for process optimization, rather than costly trial and error, has perhaps never been ...increases tool ... See full document
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Neural Network Approach to Modelling the Behaviour of Ionic Polymer Metal Composites in Dry Environments
... of artificial neural networks ...such neural networks prove to be a precise simulation tool for describing IPMC response in dry ... See full document
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ARTIFICIAL NEURAL NETWORKS AS AN EFFECTIVE PROJECT MANAGEMENT TOOL
... the artificial neural network (ANN) itself is a model because the topology and transfer functions of the nodes are usually formulated to match the current ...a neural network depends on its ... See full document
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Neural networks and non parametric methods for improving real time flood forecasting through conceptual hydrological models
... of Artificial Neural Networks (ANNs) is widely acknowledged and applications to a variety of problems, including simulation and forecasting of hydro-meteorological variables, have been presented in ... See full document
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Application of Artificial Neural Networks for Flood Warning Systems
... SAC-SMA model, which is used in the National Weather Service river forecast system, requires 20 model parameters and 6 state variables (Tokar and Markus, ...the model calibration for the conceptual ... See full document
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Title: CLASSIFICATION ON BREAST CANCER USING GENETIC ALGORITHM TRAINED NEURAL NETWORK
... training neural networks are based on local search, population methods, and others such as cooperative coevolutionary models ...to model the relationship between daily rains and runoffs in ...new ... See full document
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The Cost Forecasting Application in an Enterprise with Artificial Neural Networks
... the rates of wastage in machines and of maintenance/repair fall and as efficiency and rate of capacity use increase. Maintenance activities are directly related to these parameters. One of the most complex parts of the ... See full document
5
Artificial Neural Networks Application in Prediction of Water Quality
... The correlation co-efficient is 0.9496, 0.9892, 0.9985 for Sulphates, Chlorides, TDS respectively for ground water. Correlation co- efficient for surface waters are 0.605, 0.8703, 0.9658 respectively for sulphates, ... See full document
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ARTIFICIAL NEURAL NETWORKS – AN APPLICATION TO STOCK MARKET VOLATILITY
... Many more works have done to forecast stock market volatility using Neural Networks. Such as Karadi [1997], Aikan [1999], Edolmen [1999], Kammana [1999], Trefalis[1999], Garliauskas, A[1999], Abraham ... See full document
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Prediction of the kind of sprouts of Cruciferae family based on artificial neural network analysis
... that artificial neural networks (ANNs) are a convenient tool for predicting the kind of sprouts originated from Cruciferae ...useful tool for determining the identity of cruciferous ... See full document
6
A Comparative Study of Three Intelligent Techniques for Malaria in Africa Continent
... The model was used CLIMEX in sub-Saharan areas of Africa, by which the parasite carrier of the disease while taking into account the environmental factors affecting the lives of intermediate carrier of the disease ... See full document
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Artificial Neural Networks Application in Duplex/triplex Elevator Group Control System
... where neural network are em bedded into the D uplex/T riplex control algorithm , sim ulations are run for several levels o f interfloor traffic dem and level for the improved D u p le x /T r ip le x c o n tro l s ... See full document
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The Emissions Analysis of Diesel Engine Using GarciniaIndicaand Rice Bran Oil Based Methyl Esters As Fuels with an ANN Approach
... The results obtained from the experiments conducted for the thermal performance evaluation and emission characteristics and the performance of the neural network developed for modeling of the engine are summarized ... See full document
5
Improved the Prediction of Multiple Linear Regression Model Performance Using the Hybrid Approach: A Case Study of Chlorophyll a at the Offshore Kuala Terengganu, Terengganu
... prediction model for determining the optimal parameters for chlo- rophyll-a, data such as DO, temperature, salinity and pH was used as ...This model uses the method of adjustment tool (fitting ... See full document
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