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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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Optimization of Hyperparameters in Hybrid Deep Learning Models for Sleep Apnea Detection Using Swarm Intelligence Algorithms

کلیدواژه: Sleep Apnea, HoneyBadger Optimizer, GreyWolf Optimizer, Convolutional neural network, Deep Recurrent Neural Network

نویسندگان: Fotouhi-Ghazvini Faranak, Badiee Maryam

ناشر: پژوهش های نظری و کاربردی هوش ماشینی - Journal of Applied and Basic Machine Intelligence Research

This study investigates the efficiency of CNN-DRNN hybrid classifiers in detecting Sleep Apnea using electrocardiogram (ECG) signals. Various CNN models were evaluated, including AlexNet, VGG16, VGG19, and ZFNet, along with DRNN models such as LSTM, GRU, and BiLSTM. These models were compared with a... ادامه

سال:2025

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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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Development of Earning Manipulation Prediction Model Applying Hybrid Neural Network and Cosmology Based Algorithms

کلیدواژه: Multi-layer perceptron neural network, Cosmology algorithms, Beneish model, Corporate governance system

نویسندگان: Maleki Nia Nahid, Tehrani Reza, Tabriz Akbar Akbar, Fallah Shams Mirfeiz

ناشر: اقتصاد پولی، مالی - Monetary and Financial Economics

Extended abstract1- INTRODUCTIONAccurately predicting earning manipulation in order to detect and identify manipulation of financial statements has always been one of the most fundamental challenges ahead of financial reports users. Because of increasing financial reporting fraud, this fact resulted... ادامه

سال:2021

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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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Prediction of Meteorological Droughts in Kuhrang Using the Hybrid Model of Wavelet and Artificial Neural Network

کلیدواژه: Meteorological Drought, WANN model, ANN Model, SPI Index, RDI index, Kuhrang

نویسندگان: Bahrami Samani Marziyeh, Mirabbasi Najafabadi Rasoul, Ghasemi Dastgerdi Ahmad Reza, Abdollahi AsadAbadi Sajjad

ناشر: علوم و مهندسی آبیاری - Journal of Irrigation Sciences and Engineering

Meteorological drought is defined as a lack of rainfall over long periods, which reduces soil moisture and river flow. One of the critical drought assessment tools is drought indices (Tsakiris & Vangelis, 2005). So far, many drought indicators have been developed by researchers, for example, the RDI... 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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Hybrid Artificial Neural Network-Geostatistics Model for Urban Water Consumption Prediction. A Case Study: Osku City

کلیدواژه: Prediction,Water Consumption,Hybrid Model,Artificial Neural Network,Geostatistic,Osku City

نویسندگان: Goli Ejlali R.

ناشر: آب و فاضلاب - Water and Wastewater

The prediction of water consumption in urban basins is of immense importance for the management of water resources, especially in arid and semiarid countries. The lack of strong predictive tools, or perhaps the lack of experienced users to those tools, may contribute to problems in data interpretati... ادامه

سال:2018

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A Hybrid Model for Portfolio Optimization Based on Stock Price Forecasting with LSTM Recurrent Neural Network using Cardinality Constraints and Multi-Criteria Decision Making Methods (Case study of Tehran Stock Exchange)

کلیدواژه: Price Forecasting,LSTM,IAHP,CoCoSo,Cardinality Constraint

نویسندگان: Abdi Nasimeh, Moradzadehfard Mehdi, Ahmadzadeh Hamid, Khoddam Mahmoud

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

Due to the dynamic trend of stock prices and the volatile nature of the market, asset price forecasting plays a key role in creating an efficient strategy, and the results of price forecasting are a prerequisite for creating an optimal stock portfolio. The purpose of this study is to provide a hybri... ادامه

سال:2021

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Performance of Dragonfly Algorithm Hybrid Model - Artificial Neural Network for Modeling Settlement of Earth Dam during Construction

کلیدواژه: Construction time, Dam cross section, Dragonfly Algorithm, feature selection, Settlement

نویسندگان: Hakimi Khansar Hosein, Hosseinzadeh Dalir Ali, Parsa Javad, Shiri Jalal

ناشر: دانش آب و خاک - Water and Soil Science

Background and ObjectivesPore water pressure, stress and settlement are the most important geotechnical parameters that must be constantly monitored during the construction of earth dams. Since measuring dam settlement directly at the time of dam construction requires cost and time, the development ... ادامه

سال:2023

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