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COVID-19 Prediction Classifier Model Using Hybrid Algorithms in data mining

کلیدواژه: Accuracy,Covid-19,Classifier model,Data mining,Hybrid data mining

نویسندگان: Nikooghadam Morteza, Ghazikhani Adel, SAEEDI MOHAMMAD

ناشر: - Journal of Pediatric Perspectives - Journal of Pediatric Perspectives

Increase of stored data in medical databases needs allocative tools to get access to data, data mining, discover knowledge and efficient use of data. Medical and treatment fields are two examples of data mining tools to analyze massive data and predictive modelling. In medical sciences, prediction a... ادامه

سال:2021

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Hybrid Medical data mining Model for Identifying Tumor Severity in Breast Cancer Diagnosis

کلیدواژه: Breast Cancer Prediction,Mammography,Ultrasonography,Medical Data Mining,Invasive Ductal Carcinoma

نویسندگان: Araghi Niknam Faeze, Ghousi Rouzbeh, Masoumi AmirHossein, ATASHI ALIREZA, MAKUI AHMAD

ناشر: مهندسی صنایع - Advances in Industrial Engineering

Purpose: This study proposes a methodology for detecting tumor severity using data mining of databases relating to breast imaging modalities. In doing so, it proposes creating a software application that can serve as an efficient decision-making support system for medical practitioners, especially t... ادامه

سال:2021

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Evaluation of Hybrid Model ANN-PSO and Different data mining Methods in Estimating Monthly Evapotranspiration in Two Different Climates

کلیدواژه: Dry Regions,Evaporation and Transpiration,Machine Learning,Soft Computing

نویسندگان: Hosseini Vardanjani S.M.R., KHOSHRAVESH M., Hosseini Kakolaki S.E., Pourgholam Amiji M.

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

Evapotranspiration is one of the main components of any region's water balance. Its accurate estimation is very necessary for hydrological studies, designing irrigation and drainage systems, and planning irrigation systems. In this research, the M5 tree model, M5 Rules, K Star, Rep Tree, artificial ... ادامه

سال:2023

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A Hybrid data-mining Algorithm and dataDriven Supply Chain Modeling for Allocation Goods to Warehouses and Warehouse Service to Customers

کلیدواژه: Supply Chain,Warehouse Location,Data Mining,Warehouse Allocation,Clustering

نویسندگان: AHMADI SADRA, Yousefpour Reza

ناشر: چشم انداز مدیریت صنعتی - Industrial Management Perspective

In this research, the issue of product allocation in a situation that there are a large number customers and goods are various, is investigated. Expanding the level of Internet access and increasing the desire of online shopping, raise the number of customers. In a situation where there is a great v... ادامه

سال:2021

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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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Land Cover Change Modeling Using a Hybrid Approach and Remote Sensing data

کلیدواژه: Scenario development,Artificial neural network,Multi-objective land optimization,Markov chain,Accuracy assessment

نویسندگان: Joorabian Shooshtari Sharif

ناشر: جغرافیا و پایداری محیط - Geography and Environmental Sustainability

Wetlands are vital for human survival and constitute 40. 6% of the total value of global ecosystem services. This study analyzed land cover changes in the Golpayegan Shoor wetland from 1988 to 2018 and then modeled it with a combination of artificial neural network, Markov chain, and multi-objective... ادامه

سال:2023

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Relationship between Real Earning Management, Corporate Governance and Stock Crash Risk (Dynamic Panel data)

کلیدواژه: Stock Fall Risk,Real Earnings Management,Institutional Ownership,Dynamic Panel Data

نویسندگان: Eslami Mohsen, Erzae Amir Hossein

ناشر: سیاست های مالی و اقتصادی - Journal of Fiscal and Economic Policies

The risk of stock price crash is one of the topics of interest in capital market research. Since the main mission of capital market regulators is to protect the rights of investors, it has always been important to consider the factors that affect crash risk. The quality of financial reporting and ea... ادامه

سال:2023

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A Hybrid Approach based on PSO and Boosting Technique for data Modeling in Sensor Networks

کلیدواژه: Wireless sensor network,Distributed optimization,Particle swarm optimization,Regression,Boosting

نویسندگان: Shakibian Hadi, Nasiri Jalaledin

ناشر: - Journal of Information Systems and Telecommunication - Journal of Information Systems and Telecommunication

An efficient data aggregation approach in wireless sensor networks (WSNs) is to abstract the network data into a model. In this regard, regression modeling has been addressed in many studies recently. If the limited characteristics of the sensor nodes are omitted from consideration, a common regress... ادامه

سال:2022

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The Analysis of Effects of Good Corporate Governance on Earnings Management in Indonesia with Panel data Approach

کلیدواژه: Audit Committee,Composition of Commissioners,Good Corporate Governance,Earnings Management

نویسندگان: Muda Iskandar, Maulana Weldi, Sakti Siregar Hasan, Indra Naleni

ناشر: IRANIAN ECONOMIC REVIEW - IRANIAN ECONOMIC REVIEW

the research was aimed to analyze effects of Good Corporate Governance, comprising of Composition of Commissioners & Audit Committee on earnings management an Empirical Study on Indonesia Stock Exchange with Panel data Approach. The data collection method used was documentation. The samples in this ... ادامه

سال:2018

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Designing a Model for Implementing Digital Banking Policy Based on Using Big data in Iranian Banking Industry

کلیدواژه: policy implementation, Digital banking, Big data

نویسندگان: Gholipour Souteh Rahmatollah, Esmaeili Rad Hamed

ناشر: مدیریت دولتی - Journal of Public Administration

Objective In the current digital era, the immense challenges posed by technological advancements have driven significant developments, including the emergence of digital banking policies. For banks to survive and maintain their competitive edge among both new entrants and established competitors, i... ادامه

سال:2024

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