Search Results - (( (variable OR variables) learning through algorithm ) OR ( java application using algorithm ))
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…Furthermore, it is essential to reduce the carbon footprint of the cementitious composites through the optimization of the matrix. In this research, machine learning algorithms including regression models, tree regression models, support vector regression (SVR), ensemble regression (ER), and gaussian process regression (GPR) were utilized to predict the compressive and tensile concrete strength. …”
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Particle Swarm Optimization in Machine Learning Prediction of Airbnb Hospitality Price Prediction
Published 2022“…Choosing the best combination of the independent variables is essential, which can be achieved through features selection optimization. …”
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Depression prediction using machine learning: a review
Published 2022“…The aim of this study is to identify important variables used in depression prediction, recent depression screening tools adopted, and the latest machine learning algorithms used. …”
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Ensemble learning for multidimensional poverty classification
Published 2020“…Analysis of this study showed that Per Capita Income, State, Ethnic, Strata, Religion, Occupation and Education were found to be the most important variables in the classification of poverty at a rate of 99% accuracy confidence using Random Forest algorithm.…”
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RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
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Provider independent cryptographic tools
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Monograph -
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management
Published 2024“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…The optimized GEP as a recent extension of GEP approach is superior to other AI-based methods in giving an optimized explicit equation, which clearly shows the relationship between input historical data and EEC in different countries without prior knowledge about the nature of the relationships between independent and dependent variables. This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through use of a robust and efficient optimization algorithm in learning process of GEP approach. …”
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Thesis -
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The determinant factors for the issuance of Central Bank Digital Currency (CBDC) in Malaysia using machine learning framework
Published 2024“…The overall Central Bank Digital Currency Project Index (CBDCPI) was selected as a target variable, while two machine learning algorithms, Random Forest and XGBoost were utilized to identify the determining variables. …”
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A case study on quality of sleep and health using Bayesian networks
Published 2012“…There are several phases involved including implementation of the learning algorithms, integration of prior knowledge through the whitelist argument and arc setting to form directed acyclic graphs. …”
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Short-term electricity price forecasting in deregulated electricity market based on enhanced artificial intelligence techniques / Alireza Pourdaryaei
Published 2020“…This merit is provided by balancing the exploitation of solution structure and exploration of its appropriate weighting factors through the use of Backtracking Search Algorithm (BSA) as an efficient optimization algorithm in learning process of ANFIS approach. …”
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Neural Network Multi Layer Perceptron Modeling For Surface Quality Prediction in Laser Machining
Published 2009“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves using a computer algorithm to capture hidden knowledge from data. …”
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Book Chapter -
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Integration of machine learning and remote sensing for above ground biomass estimation through Landsat-9 and field data in temperate forests of the Himalayan region
Published 2024“…Secondly, the research systematically assesses the effectiveness of different algorithms to identify the most precise method for establishing any potential relationship between field-measured AGB and predictor variables. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration
Published 2022“…The works presented in the thesis strive to solve the data hunger of machine learning models through the integration of data fusion techniques, with a minimalistic approach by using simple yet robust models. …”
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Artificial Intelligence (AI) to predict dental student academic performance based on pre university results
Published 2021“…Machine Learning Algorithm is applied using academic result samples of graduates of the Kulliyyah of Dentistry, IIUM from 2016-2021. …”
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Proceeding Paper -
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Short-Term Electricity Price Forecasting via Hybrid Backtracking Search Algorithm and ANFIS Approach
Published 2019“…Through the combination of backtracking search algorithm (BSA) in learning process of ANFIS approach, a hybrid machine learning algorithm has been developed to forecast the electricity price more accurately. …”
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