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Modeling Groundwater Level in Delfan plain, Lorestan Province, Using Hybrid Metaheuristic Models

کلیدواژه: Groundwater Level, Artificial neural network, Metaheuristic optimization, Delfan plain

نویسندگان: Nohani Ebrahim, Babaali Hamidreza, Dehghani Reza

ناشر: آبخوان و قنات - Journal of Aquifer and Qanat

Groundwater is often a crucial source of freshwater worldwide, particularly in arid and semi-arid regions. In these areas, Groundwater resources are vital due to variable rainfall and high evaporation rates. Groundwater use is increasing in arid and semi-arid regions due to population growth, rapid ... ادامه

سال:2024

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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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Hybrid Learning Machine Metaheuristic Model for Estimating Groundwater Level

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

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Application of Artificial neural network Hybrid Models with Metaheuristic Algorithms (PSO, ICA) in Earnings Management Forecast

کلیدواژه: Particle Swarm Optimization,Imperialist Competitive Algorithm,Artificial neural network,Earnings Management

نویسندگان: GHADERI EGHBAL, AMINI PEYMAN,

ناشر: پژوهش های تجربی حسابداری - Journal of Empirical Research in Accounting

Metaheuristic approaches are inspired mainly based on the order and rules of natural organisms. Today, these approaches have been widely used in various branches. According to the importance of forecasting, understanding the methods of earnings management forecast can provide useful information for ... ادامه

سال:2020

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Assessment of Groundwater Hardness in Khorramabad plain Using Hybrid Models Based on Metaheuristic Algorithms

کلیدواژه: Groundwater, Khorramabad, Support Vector Regression, Metaheuristics

نویسندگان: Babaali Hamidreza, Nohani Ebrahim, Dehghani Reza

ناشر: آبخوان و قنات - Journal of Aquifer and Qanat

Introduction: Over the past century, water scarcity has become a significant global issue due to climate change, population growth, urbanization, and agriculture. In response to this problem, Groundwater resources have been used extensively for various purposes, including agriculture, industry, and ... ادامه

سال:2024

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Estimation of Reference Evapotranspiration Using Artificial neural network Models and the Hybrid Wavelet neural network

کلیدواژه: Water Requirement,Davbechies Wave-let,Temperature,Statistical Indices,Shahrekord

نویسندگان: GANJI KHORRAMDEL N., Hoseini S. M. R.

ناشر: علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی) - Journal of Water and Soil Science

Estimation of evapotranspiration is essential for planning, designing and managing irrigation and drainage schemes, as well as water resources management. In this research, Artificial neural networks, neural network wavelet model, multivariate regression and Hargreaves' empirical method were used to... ادامه

سال:2019

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Predicting Corporate Financial Distress Using a Hybrid Model of Artificial Immune System and Wavelet neural network (Artificial Intelligence)

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

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Spatial-Temporal Disaggregation of Rainfall Time Series Using Wavelet-Artificial neural network Hybrid Model

کلیدواژه: Rainfall Time Series,Disaggregation,Artificial Neural Networks,Wavelet Transform,Hybrid Model

نویسندگان: Farboudfam N., NOURANI V., AMINNEJAD B.

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

Due to the need to simulate rainfall time series at different time scales for engineering purposes on one hand and lack of recordings for these parameters in small scales caused by the administrative and financial problems, on the other hand, disaggregation of rainfall time series to the desired sca... ادامه

سال:2019

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Evaluation of the Accuracy of Wavelet-Neuro-Fuzzy, Neuro-Fuzzy, and Wavelet Hybrid Models in Groundwater Level Prediction (Case Study: Birjand plain)

کلیدواژه: Wavelet analysis, Groundwater Level, Birjand plain, Fuzzy Neural Network, Water resources management

نویسندگان: Dastuorani Mehdi, Khayat Amir, Akhondi Zahra

ناشر: آبخوان و قنات - Journal of Aquifer and Qanat

Given the scarcity of water resources and the importance of their optimal management, accurate prediction of Groundwater Level fluctuations is essential. Intelligent models such as time series, wavelet analysis, Artificial neural networks, and support vector machines can help in the sustainable u... ادامه

سال:2024

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The Application of Metaheuristic optimization Algorithms of Gravitational Search, Particle Swarm, and their Hybrid in Fracture network Modeling

کلیدواژه: Fractured Network Modeling,Multivariate Optimization Algorithms Particle Swarm Optimization,Gravitational Search Algorithm

نویسندگان: SHAKIBA Sima, DOULATI ARDEJANI FARAMARZ

ناشر: پژوهش نفت - PETROLEUM RESEARCH

Fractured network modeling is the main prerequisite for fluid flow simulation in many applications such as Groundwater resource management, oil and gas reservoir simulation, geothermal energy resource modeling and etc. The aim of this study is to develop an iterative object-based algorithm for fract... ادامه

سال:2023

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