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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
مشاهده/دانلود
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
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
کلیدواژه: SVM,Wavelet transfor,SOM,Groundwater,Ardabil plain
نویسندگان: Daneshvar Vousoughi Farnaz, Manafian azar Vahid
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
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
کلیدواژه: Groundwater level,Weighted least square support vector machine,Particle swarm optimization,Gravitational search algorithm-Efficiency
نویسندگان: Khosravi Shiva, Robati Amir
ناشر: مهندسی عمران مدرس - Modares Civil Engineering journal
Groundwater is the most reliable source of supply for potable water and supports a wide array of economic and environmental services. There is a significant concern that groundwater levels are declining due to intense aquifer use. The sustainable management of groundwater resources requires good pla... ادامه
سال:2021
کلیدواژه: Financial Distress,Financial Prediction,Wavelet Neural Network,Artificial Immune System,Logistic Regression,Hybrid Algorithm
نویسندگان: Mehrabi Reza, Hematfar Mahmoud, Sefati Farid
ناشر: تکنولوژی در کارآفرینی و مدیریت استراتژیک - Journal of Technology in Entrepreneurship and Strategic Management
In today's financial landscape, the prediction of corporate financial distress plays a crucial role in risk management and economic stability. This study aims to develop a hybrid predictive model that combines the Artificial Immune System (AIS) with the Wavelet Neural Network (WNN) to forecast finan... ادامه
سال:2024
کلیدواژه: Watershed Land Use Change,Conceptual Rainfall-Runoff Model,Storage Coefficients,Artificial Intelligence,Wavelet-Entropy
نویسندگان: ANDALIB GHOLAMREZA, NOURANI VAHID, Sharghi Elnaz
This research investigated LULC changes and its effect on outlet runoff by detecting LULC changes location and severity via an inverse method for the Little River Watershed, USA. In this research, the Artificial intelligence and soft computing capabilities such as wavelet-entropy were employed for t... ادامه
کلیدواژه: Artificial intelligence,Groundwater aquifer,Hybrid model,Kabodarahang,Simulation
نویسندگان: MALEKZADEH MARYAM, KARDAR SAEID, SHABANLOU SAEID
ناشر: تحقیقات آب و خاک ایران - Iranian Journal of Soil and Water Research
In present study, the groundwater level of the Kabodarahang region located in Hamadan Province was simulated using novel techniques such as Self-Adaptive Extreme Learning Machine (SAELM) and WaveletSelf-Adaptive Extreme Learning Machine (WA-SAELM). Firstly, the effective lags were detected using the... ادامه
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
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