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Investigating the Application of Hybrid Support Vector Machine Models in Predicting River Flow of Karkhe Basin

کلیدواژه: Bayesian Network,Support Vector Machine,Wavelet,Karkhe Basin

نویسندگان: DEHGHANI REZA, Torabi Poodeh Hasan, YOUNESI HOJJATOLLAH, Shahinejad Babak

ناشر: هیدروژئومورفولوژی - HYDROGEOMORPHOLOGY

Introduction: River flow forecasting is one of the most important issues in water resources management and planning, especially in making the right decisions in the event of floods and droughts. Various approaches to hydrology have been introduced to predict river flow rates, among which, intelligen... ادامه

سال:2020

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Aplication of the Hybrid Model of Support Vector Machine-Algorithm Artificial Flora in Estimating the Daily Flow of Rivers (Case study: Dez Basin)

کلیدواژه: Artificial Flora Alghorithm,Prediction,Dez Basin,Support Vector Machine

نویسندگان: DEHGHANI R., TORABI POUDEH H., YOUNESI H., SHAHINEJAD B.

ناشر: تحقیقات منابع آب ایران - Iran-Water Resources Research (IWRR)

In this study, the hybrid support Vector machine-artificial flora algorithm method was developed and the results were compared with those of the support Vector machine-wavelet model. The case study of Dez catchment area was used in order to estimate the flow rate of the rivers employing the daily di... ادامه

سال:2020

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Investigating the Effect of Providing Banking Facilities within the Framework of Islamic Contracts on the Value Added of Economic Sectors: Application of the Bayesian Vector Autoregression Model (BVAR)

کلیدواژه: Banking contracts,Islamic banking,Islamic contracts,Value added of economic sectors,Bayesian vector autoregression model

نویسندگان: Nasr Esfahani Mohammad, GHAEMI ASL MEHDI, Zare Kordiani Ali Asghar

ناشر: معرفت اقتصاد اسلامی - Ma`rifat-e Eghtesad-e Islami

In the interest-free banking system, Islamic contracts, due to their operational nature and interactivity with other economic sectors, can help guide and organize private sectors of the economy. This paper studies the effect of banking facilities within the framework of the Islamic contracts of Ju'a... ادامه

سال:2019

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Development of Hybrid Bayesian Network Model for Multi-Hazards Risk Assessment of Irrigation Network

کلیدواژه: Risk Assessment,Agricultural Water System,Improper Performance of the Ditch-Riders,Operational Losses,Roodasht Irrigation Network

نویسندگان: BOZORGI ATIYEH, ROOZBAHANI ABBAS, HASHEMY SHAHDANY MEHDY

ناشر: تحقیقات آب و خاک ایران - Iranian Journal of Soil and Water Research

Since the majority of water resources is used for agricultural purposes, irrigation and drainage networks become important. Moreover, these networks are threatened by various natural and unnatural hazards that each one can affect the performance of the network. This research seeks to develop a risk ... ادامه

سال:2021

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Prediction of Monthly River Flow Using Hybridization of Linear Time Series Models and Bayesian network (Case Study: Bakhtiari River)

کلیدواژه: Bayesian network,Input pattern,Model development,Stationary test

نویسندگان: AHMADI FARSHAD, VALINIA MIR MAHMOOD

ناشر: مدیریت آب و آبیاری - Journal of Water and Irrigation Management

One of the most important issues in water resources management is the preparation and development of appropriate models in order to predict the streamflow more accurately. For this purpose, in the present study, linear time series models (ARMA), intelligent Bayesian network (BN) and BN-ARMA hybrid m... ادامه

سال:2020

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Using Hybrid Wavelet-Support Vector Machine and Wavelet-Neural Network Models for Groundwater Level Prediction in Ardabil Plain

کلیدواژه: SVM,Wavelet transfor,SOM,Groundwater,Ardabil plain

نویسندگان: Daneshvar Vousoughi Farnaz, Manafian azar Vahid

ناشر: هیدروژئومورفولوژی - HYDROGEOMORPHOLOGY

Groundwater has played an important role in the urban and rural water supply and agriculture. In order to manage water resources, an accurate and reliable groundwater level forecasting is needed. In this research, 15 piezometers in Ardabil plain were used. SVM was applied for a prediction method in ... ادامه

سال:2019

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Investigation of Dissolved Oxygen Levels in the Karun River Water Using Hybrid Models Based on Support Vector Regression

کلیدواژه: Dissolved Oxygen, Support vector regression, Karun, Modeling

نویسندگان: Babaali Hamidreza, Nohani Ebrahim, Dehghani Reza

ناشر: هیدروفیزیک - HYDROPHYSICS

Oxygen plays a vital role in maintaining the balance of life cycles in all ecosystems. Aquatic life is highly sensitive to dissolved oxygen (DO) levels. This necessitates not only continuous monitoring of DO in aquatic environments but also the development of accurate predictive models for future DO... ادامه

سال:2024

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The Potential of the Hybrid Support Vector Regression Model for Predicting River Sediment Discharge (Case Study: Keshkan-Lorestan River)

کلیدواژه: Kashkan, Support vector regression, suspended sediments, Modeling

نویسندگان: Babaali Hamidreza, Nohani Ebrahim, Dehghani Reza

ناشر: هیدروفیزیک - HYDROPHYSICS

Providing a robust and reliable predictive model for river sediment discharge is an essential task for several environmental and geomorphological perspectives, including water quality, riverbed engineering sustainability, and aquatic habitats. In this research, a new hybrid intelligent approach base... ادامه

سال:2023

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Hybrid Model Binary ant Colony Algorithm and Support Vector Machine (BACO-SVM) for Feature Selection and Classification of Bank Customers with Case Study

کلیدواژه: credit risk,credit rating,support vector machine,feature selection,Binary ACO,VIKOR

نویسندگان: HUSSEINZADEH KASHAN ALI, GAROUSI FATEMEH

ناشر: راهبرد مدیریت مالی - JOURNAL OF FINANCIAL MANAGEMENT STRATEGY

One of the most important issues faced by banks and financial institutions is the issue of credit risk. The significant amount of deferred bank claims around the world indicates the importance of this issue and the need to pay attention to it. So far, many efforts have been made to provide an effect... ادامه

سال:2020

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Development of Hybrid Wavelet-Artificial Neural Network and Support Vector Machine Approach for Multi-Station Rainfall-Runoff Modeling Using Clustering and Mutual Information Tools

کلیدواژه: Mutual information,Wavelet transform,Little River watershed,Self-organizing map,Artificial intelligence

نویسندگان: ANDALIB GHOLAMREZA, NOURANI VAHID, Monirifar Hosein, Sharghi Elnaz

ناشر: رویکردهای نوین در مهندسی عمران - JOURNAL OF NEW APPROACHES IN CIVIL ENGINEERING

Conversion of rainfall to runoff according to the laws of gravity vivifies earth, replenishes groundwater, keeps rivers and lakes full of water, and varies the landscape by the action of erosion. Large uncertainties and high non-linearity of the Rainfall-Runoff (R-R) process make it complex task to ... ادامه

سال:2019

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