[PDF] Top 20 Flood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
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Flood Forecasting Using Artificial Neural Networks: an Application of Multi-Model Data Fusion technique
... this model an MLP network with two inputs of discharge at time steps (t-1) and (t-2) were used for training the discharge at time step ...the data around the bisector line as depicted in Fig.3 shows that ... See full document
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Application of Artificial Neural Networks in Weather Forecasting: A Comprehensive Literature Review
... applied Artificial Neural Network for determination of Distributed Rainfall- Runoff Model Parameters and they found that the ANN technique can be successfully employed for the purpose of ... See full document
13
Application of Artificial Neural Networks for Flood Warning Systems
... of data collection and expected to provide high-quality, high-resolution precipitation data for the United ...NEXRAD data provides a new approach of rainfall-runoff modeling, storm forecast, and, ... See full document
151
Applicability of the Deep Learning Flood Forecast Model Against the Inexperienced Magnitude of Flood
... of flood forecasting is critical in reducing the damage that can occur during flood ...the flood prediction system is in operation in the first class rivers in Japan, prediction accuracy is ... See full document
7
Artificial Neural Network Models Investigation for Euphrates River Forecasting & Back Casting
... the data –driven techniques, and have been widely used in stream flow ...for forecasting tasks (Maier and Dandy, 2000; Samarassinghe, ...ANN artificial neural networks model for ... See full document
15
Classification of hydro meteorological conditions and multiple artificial neural networks for streamflow forecasting
... the application of a modu- lar approach for real-time streamflow forecasting that uses different system-theoretic rainfall-runoff models according to the situation characterising the forecast ...specific ... See full document
12
Data Mining using Neural Networks
... enormous data and it need to have tremendous processing power by the servers to maintain this valuable data and ...to data storage Erasure coding exhibits much success in the area of data ... See full document
6
Data driven Time Series Based Prediction in Smart Home Appliance Energy Consumption
... Besides the use of electrical appliances and devices in buildings, the geographical locations of a building also influence the electric energy consumption, and indirectly affects the forecasting analy- sis. ... See full document
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Article Description
... the neural network and a corresponding desired or target response set at the output (when this is the case the training is called ...the data. If one does not have data that cover a significant ... See full document
7
A Review of Epidemic Forecasting Using Artificial Neural Networks
... of ANN performance, hybrids of ANN are usually used. This study is organized into four sections. Section one provides an introduction to the necessity of making the right choice for epidemic forecast methodology. In ... See full document
12
FCM BPSO: ENERGY EFFICIENT TASK BASED LOAD BALANCING IN CLOUD COMPUTING
... Weather forecasting is a challenging time series forecasting problem because of its dynamic, continuous, data-intensive, chaotic and irregular ...series forecasting techniques exist and are ... See full document
13
Prediction of indoor environmental parameters for naturally ventilated building using artificial neural network: a reflection of outdoor parameters
... membangunkan model ramalan bagi meramal parameter persekitaran dalaman dengan menggunakan teknik Rangkaian Neural ...mendapatkan data dalaman dan luaran sebenar; dan untuk menyediakan data ... See full document
52
Application of Artificial Neural Network And Multiple Linear Regression Model for Forecasting of Container Throughput In APM Terminals Apapa Port A Comparative Approach
... Over 90% of world trade is carried by shipping industry (Shipping Facts 2012). Liner shipping is considered as a scheduled shipping service of containerized cargo between this challenges, it is indispensable to use new ... See full document
16
Data Fusion Using Different Activation Functions in Artificial Neural Networks for Vehicular Navigation
... The input layer is the set of source nodes (sensory units).The second layer is a hidden layer of high dimension. In the hidden layer Euclidean distance (represented as ||…||) is calculated and most commonly used Gaussian ... See full document
15
Review on Financial Forecasting Using Neural Network and Data Mining Technique
... Is the process of identifying a set of common features and models that describe and distinguish data classes or concepts. The models are used to predict the class of objects whose class label is unknown. A bank, ... See full document
5
Study on Pollution Forecasting using 2Phase Neural Network
... of Neural Network :It is apparent that a neural network derives its computing power through, first, its massively parallel distributed structure and, second, its ability to learn and therefore ...the ... See full document
7
Resolving the effect of wrist position on myoelectric pattern recognition control
... including data from too many wrist positions may increase error ...muscle data for non-amputees, Subject 1, and Subject 2 ...cause data from one wrist position had class labels that directly ... See full document
11
Inflation Forecasting in Pakistan using Artificial Neural Networks
... An artificial neural network (hence after, ANN) is an information- processing paradigm that is inspired by the way biological nervous systems, such as the brain, process ...series forecasting, have ... See full document
19
Fuzzy PCA Hybrid Approach For Image Fusion Using Laplacian Features
... sensor fusion is Artificial Neural Network (ANN) and Fuzzy Logic ...this technique output decision is taken on the basis of trained input ...input data set with the output ...input ... See full document
10
The Cost Forecasting Application in an Enterprise with Artificial Neural Networks
... that Artificial Neural Networks are computer programs that imitate the function of learning which runs in the human ...an Artificial Neural Network is being trained, it requires an ... See full document
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