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Modeling of River Quality Parameters Using Hybrid Time Series Models (Case Study: Gedarchay River)

کلیدواژه: Contemporaneous Models,Linear Models,Multivariate Models,Time series,Water Quality

نویسندگان: Sepehri L., KHALILI K.

ناشر: آبیاری و زهکشی ایران - Iranian Journal of Irrigation and Drainage

In this research, in order to study and evaluate the accuracy of single-variable time series models, multivariables time series and hybrid models in modeling the River flow quality values in the Peygale hydrometric station located in the west of Lake Urmia from data The qualitative flow of the River... ادامه

سال:2019

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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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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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Watershed Change Detection Using Hybrid Conceptual Model-Artificial intelligence

کلیدواژه: Watershed Land Use Change,Conceptual Rainfall-Runoff Model,Storage Coefficients,Artificial Intelligence,Wavelet-Entropy

نویسندگان: ANDALIB GHOLAMREZA, NOURANI VAHID, Sharghi Elnaz

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

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

سال:2019

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Evaluating Performance of Hybrid Neural Network Models in Daily River Flow Estimation

کلیدواژه: Flow Discharge,Support Vector Machine,Wavelet Neural Network,Forecasting

نویسندگان: Younesi Hojatolah, GODARZI AHMAD

ناشر: ENVIRONMENTAL RESOURCES RESEARCH - ENVIRONMENTAL RESOURCES RESEARCH

River flow forecasting is of immense importance for reliable planning, designing, and management of water resources projects. This study investigated the performance of wavelet neural network, support vector machine, artificial neural network, and Multiple Models Driven by Artificial Neural Networks... ادامه

سال:2021

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Identifying Best Ideas in Iranian Mutual Funds

کلیدواژه: Best Ideas, Portfolio Performance, Mutual Funds

نویسندگان: Heidari Mahdi, Marashi Ali

ناشر: تحقیقات مالی - Financial Research Journal

Objective
Best ideas refer to trades within Mutual funds that are driven by the goal of outperforming the index and are primarily based on expert analysis. According to the extant literature, in this study, we use four measures to detect the best ideas... ادامه

سال:2024

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Performance Persistence Investigation in Equity Mutual Funds

کلیدواژه: Performance Persistence,Manipulation-Proof Performance Measure,Mutual Fund

نویسندگان: Hosseini Mahsa, KHODAEI VALAHZAGHARD MOHAMMAD, SAEEDI ALI

ناشر: چشم انداز مدیریت مالی - JOURNAL OF FINANCIAL MANAGEMENT PERSPECTIVE

The aim of this research is to investigate performance persistence in equity Mutual funds at 1 and 12-month horizons. To this end, the Manipulation-Proof Performance Measure (MPPM) derived by Goetzmann et al. (2007) along with a number of current performance measures such as Treynor, Sharpe, Jensen&... ادامه

سال:2019

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Liquidity Risk Management Framework of Mutual Funds

کلیدواژه: Mutual funds, Liquidity Risk Management, Liquidity Risk Management Tools

نویسندگان: Hosseini Seyed Hossein, Ebrahimi Sarv Oliya Mohammad Hassan, Amiri Maysam, Peymanifurushani Moslem

ناشر: مدیریت دارایی و تامین مالی - Journal of Asset Management and Financing

 
The possibility of repurchasing the investment units issued by the fund is a distinctive feature of open-end Mutual funds, which exposes these funds to liquidity risk. The main challenge of liquidity management of these funds is providing cash during a crisis and also facing ... ادامه

سال:2023

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Control or Innovation; Legal Requirements of Regulatory Policies in Artificial intelligence

کلیدواژه: Artificial Intelligence (AI),legislation,Regulation,Regulatory Policy,Risk and Control,opportunity and Innovation

نویسندگان: Hashemi Seyed Hossein

ناشر: دولت و حقوق - Government and Law

In response to the rapid development of artificial intelligence (AI), various legal systems have created different regulatory and supervisory interventions for this technology. While some countries prioritize consumer protection by imposing stringent regulations, others adopt a more permissive appro... ادامه

سال:2024

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The Effects of Stale Prices on Mutual Funds

کلیدواژه: Equity Mutual Funds, Fair Price, Fund Flow, Stale Prices, Wealth Transfer

نویسندگان: Ebrahimnejad Ali, Barakchian Seyyed Mahdi, Aliabadi Farahani Ebrahim

ناشر: مدیریت دارایی و تامین مالی - Journal of Asset Management and Financing

Daily liquidity to investors is promised by Mutual funds, which allows them to redeem their money based on the prevailing Net Asset Value (NAV). A number of factors like trading suspension and daily price limits can cause redeemed NAV to deviate from the intrinsic values of fund units. Such “stalene... ادامه

سال:2022

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