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 Hydrological Predictions. Using Data-Driven Models Coupled with Data Preprocessing Techniques
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Hydrological Predictions. Using Data-Driven Models Coupled with Data Preprocessing Techniques

автор Kwok-wing C. издательство Книга по Требованию Книги
Cтраниц 248        мягкая обложка       
Аннотация:Four data-preprocessing methods including moving average (MA), principal component analysis (PCA), singular spectrum analysis (SSA), and wavelet analysis (WA), are further investigated by integration with the abovementioned forecasting models. Representative models, such as K-nearest-neighbors (K-NN) model, dynamic system based model (DSBM), ANN, modular ANN (MANN), and hybrid artificial neural network-support vector regression (ANN-SVR), are then proposed to conduct rainfall and streamflow forecasts. This book makes an endeavor to improve the accuracy of hydrological forecasting in three aspects, model inputs, selection of models, and data-preprocessing techniques. Seven input techniques, namely, linear correlation analysis (LCA), false nearest neighbors, correlation integral, stepwise linear regression, average mutual information, partial mutual information, artificial neural network (ANN) based on multi-objective genetic algorithm, are first examined to select optimal model inputs in each prediction scenario.
Автор: Kwok-wing C.
Издательство: Книга по Требованию
Год:2010
Цена:
3050 руб
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Поиск: Hydrological Predictions. Using Data-Driven Models Coupled with Data Preprocessing Techniques
НОВЫЙ ГОД СИМВОЛ 2013 ГОДАУКРАШЕНИЯ
КАРНАВАЛ НА НОВЫЙ ГОД РАСПРОДАЖА
Ортомолекулярная медицина Orthomol Устрание причин заболеваний. Ортомоль это новый метод для лечения и профилактики болезней. Orthomol - ортомолекулярная медицина.
Evaluating the GPRS Radio Interface for Different Quality of Service...

I co ras o he models developed i , our approach addi io ally represe s he mobili y of users hrough arrival ra es of ew GSM a d GPRS users as well as ha dover ra es of GSM a d GPRS users from eighbori g cells. Fur hermore, we co sider users wi h differe QoS profiles modeled by a weigh ed fair queuei g scheme accordi g o . he remai der of he paper is orga ized as follows. Sec io 2 describes he basic GPRS e work archi ec ure, he radio i erface, a d differe QoS profiles, which will be co sidered i he simula or. I Sec io 3 we describe he sof ware archi ec ure of he GPRS simula or, de ails abou he mobili y of GSM a d GPRS users, he way we modeled quali y of service profiles, a d he workload model we used. Resul s of he simula io s udies are prese ed i Sec io 4. We provide curves for average carried raffic a d packe loss probabili ies for differe cha el alloca io schemes a d packe priori ies as well as curves for average hroughpu per GPRS user.3 he Simula io Model We co sider a clus er comprisi g of sever hexadiago al cells i a i egra ed GSM/GPRS e work, servi g circui -swi ched voice a d packe -swi ched da a calls. he performa ce s udies prese ed i Sec io 4 were co duc ed for he i ermos cell of he seve cell clus er.
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