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Application of Hybrid Data Mining Model (Genetic Algorithm-Wavelet-Deep Neural Network-Monte Carlo Method) for Forecasting the Price of Agricultural Products: A Case Study of Future Price of Saffron in Agricultural Commodity Exchange

کلیدواژه: Forecasting, Future Price of Saffron, Genetic algorithm, Wavelet Theory, Deep learning Neural Network, Monte Carlo Method

نویسندگان: Heydari Reza, Haj Seyed Javady Seyed Mohammad Reza

ناشر: اقتصاد کشاورزی و توسعه - Journal of Agricultural Economics and Development

The Price Forecasting and its changes trend is one of the most important factors in decision making and formulating strategies related to agricultural products. This study aimed at presenting a Hybrid data mining Model for accurate Price Forecasting of agricultural products, including nonlinear mode... ادامه

سال:2023

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Comparison of Stock Index Forecasting Using Hybrid Models Based on Genetic Algorithm and Harmonic Search with Artificial Neural Network

کلیدواژه: Genetic Algorithms,Harmony Search,Artificial Neural Networks

نویسندگان: DAVALLOU MARYAM, Heidari Toktam

ناشر: اقتصاد مقداری - Journal of Quantitative Economics

This paper is aimed to compare stock index Forecasting using Hybrid Models based on Genetic Algorithm (GA) and Harmonic Search (HS) with Artificial Neural Network (ANN). The most relevant technical indicators as inputs and the optimal number of neurons in hidden layer of Artificial Neural Network de... ادامه

سال:2018

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Optimization and Modeling of Plasma Cutting of AISI 309 Stainless Steel by Using Neural Network-Genetic Algorithm Hybrid Model

کلیدواژه: Plasma cutting,ANN,Kerf,HAZ,Ra

نویسندگان: Mirabdolahi S.M., ABOOTORABI M.M.

ناشر: مهندسی مکانیک مدرس - Modares Mechanical Engineering

In plasma cutting, a noble gas at high speed is blown from the nozzle and ionized with the help of a frequency spark at high voltage and an electric arc is created which cause the gas changes to the plasma state. Plasma cutting is an ideal process for cutting of the hard metals. In this research, th... ادامه

سال:2019

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Probabilistic Modeling and Estimation of Flow Rate of Sewage Treatment Plant Using Monte Carlo Hybrid Method

کلیدواژه: Probability Distribution,Monte Carlo,Lognormal,Fourier Series,Wastewater Inflow

نویسندگان: PIRI J., PIRZADEH B., KESHTEGAR B., GIVEHCHI M.

ناشر: آب و فاضلاب - Water and Wastewater

One of the most important results of hydraulic and hydrological Modeling of the urban drainage Network is hydrograph estimation. Annual journals on hydraulic and hydrological problems, especially in developing countries, are full of missing data, discrete and continuous gaps in most hydrological dat... ادامه

سال:2020

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Designing The Most Suitable Hybrid Model for Forecasting The Future Price of Saffron in The Agricultural Commodity Exchange

کلیدواژه: Saffron Price Forecasting , Hybrid Model ,Genetic Algorithm , Deep Neural Network and Monte Carlo Method

نویسندگان: Haj Seyed Javadi Seyed Mohammad Reza, Heydari Reza

ناشر: تحقیقات اقتصاد و توسعه کشاورزی ایران - Iranian Journal of Agricultural Economics and Development Research

Saffron, as the most expensive agricultural and medicinal product in the world, has a special place in buying and selling related to the Iranian agricultural commodity bourse. The Saffron commodity bourse, like any other market, has always faced limitations and structural problems, and most of these... ادامه

سال:2022

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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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The efficiency of Data-Driven Models for Months ahead Groundwater Level Forecasting Using a Hybrid Gamma Test and Genetic Algorithm Model

کلیدواژه: Groundwater levels,Gamma Test,Artificial neural network,SVR,Genetic Algorithm

نویسندگان: mirarabi ali, Naseri Hamidreza, NAKHAEI MOHAMMAD, Alijani Farshad

ناشر: زمین شناسی کاربردی پیشرفته - ADVANCED APPLIED GEOLOGY

In order to implement sustainable groundwater resources management, it is necessary to Model the behavior of groundwater level. Groundwater is a nonlinear and complex system which Data-driven Models can be Modeled this system without approximation and simplification. This study evaluates the perform... ادامه

سال:2018

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Developing a Hybrid Model to Estimate Expected Return Based on Genetic Algorithm

کلیدواژه: The results show that applying the hybrid model increases the predictive power of realized return compared to other research models

نویسندگان: Asima Mehdi, Abbaszadeh Asl Amir Ali

ناشر: تحقیقات مالی - Financial Research Journal

Objective: Capital asset pricing Model (CAPM) has been among the most common Models to estimate the expected return. In the standard CAPM Model, a) the beta coefficient is fixed and b) the relationship between stock returns and market returns is assumed to be linear. While in financial markets, it i... ادامه

سال:2019

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Applying Hybrid Models Based on Deep Machine Learning in Smart Agriculture (Case study: Forecasting the Future Price of Pistachios)

کلیدواژه: Datamining, Deep learning neural network, Future price forecast, Monte Carlo-Markov chain, Wavelet theory

نویسندگان: Haj Seyedjavadi S.M.R., Heydari R.

ناشر: اقتصاد و توسعه کشاورزی - Journal of Agricultural Economics & Development

Introduction The agricultural sector is one of the most basic and vital component in the social and economic structures of any country. Today, with increasing in the world's population and needing to provide food on the other hand, and increasing in the Price fluctuations of agricultural products on... ادامه

سال:2023

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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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