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A Hybrid Approach Based on Seasonal autoregressive Integrated Moving Average and Neural network autoregressive Models to Predict Scorpion sting Incidence in El Oued Province, Algeria, From 2005 to 2020

کلیدواژه: El Oued province,Neural network autoregressive model,Prediction,SARIMA model,Scorpion sting

نویسندگان: Zenia Safia, L’Hadj Mohamed, Selmane Schehrazad

ناشر: JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS) - JOURNAL OF RESEARCH IN HEALTH SCIENCES (JRHS)

Background: This study was designed to find the best statistical approach to scorpion sting predictions. Study Design: A retrospective study. Methods: Multiple regression, seasonal autoregressive integrated moving average (SARIMA), neural network autoregressive (NNAR), and hybrid SARIMA-NNAR models ... ادامه

سال:2023

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Development of Hybrid Bayesian network Model for Multi-Hazards Risk Assessment of Irrigation network

کلیدواژه: Risk Assessment,Agricultural Water System,Improper Performance of the Ditch-Riders,Operational Losses,Roodasht Irrigation Network

نویسندگان: BOZORGI ATIYEH, ROOZBAHANI ABBAS, HASHEMY SHAHDANY MEHDY

ناشر: تحقیقات آب و خاک ایران - Iranian Journal of Soil and Water Research

Since the majority of water resources is used for agricultural purposes, irrigation and drainage networks become important. Moreover, these networks are threatened by various natural and unnatural hazards that each one can affect the performance of the network. This research seeks to develop a risk ... ادامه

سال:2021

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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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New Approach for Prediction of Water Distribution network Pipes Failure Based on a Intelligent Hybrid Model (Case Study: Gorgan Water Distribution network)

کلیدواژه: Gorgan,Hybrid Model,Intelligent Model,Pipe Failure Rate,Urban Water Distribution Network

نویسندگان: JAFARI S.M., ZAHIRI A., BOZORG HADAD O., MOHAMMAD REZAPOUR TABARI M.

ناشر: پژوهش های حفاظت آب و خاک - Journal of Water and Soil Conservation

Background and Objectives: Urban water distribution networks consider as one of the essential infrastructural facilities and equipment in urban areas. The pipes are one of the primary and essential components of a water distribution network break during operation due to various factors. So, developi... ادامه

سال:2021

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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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Developing a Model for Policy Making in Digital Banking, Based on network Approach

کلیدواژه: Public Policy Making,Smart Economy,Digital Banking,Network Policy Making,Digital Banking Policy Making Actors

نویسندگان: Ghadami Mehdi, MOUSAKHANI MORTEZA, Alwani Sayyed Mehdi, yazdani hamidreza

ناشر: سیاستگذاری عمومی - IRANIAN JOURNAL OF PUBLIC POLICY

networks are considered as tools of collaboration between different sections of society. Using networks, all stakeholders can be involved in the policy-making process. The digitalization of the economy in general and the banking industry in particular, is among the phenomena of the present age. The ... ادامه

سال:2022

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Designing and Illustrating the Knowledge network of Digital Banking Studies with a Bibliometric Approach

کلیدواژه: Digital Banking, Bibliometrics, Knowledge network, Illustration

نویسندگان: Farokhizadeh Farshid, Zarei Azim, Rastgar Abbasali, Ebrahimi Seyed Abbas

ناشر: پژوهش نامه علم سنجی - Scientometrics Research Journal

Purpose: In the age of information, the increasing competition among banks to gain a larger share of the monetary and financial market has led to a more detailed and profound focus on the needs and demands of customers. Achieving maximum customer satisfaction initia... ادامه

سال:2024

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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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