Search Results - (( data integration acs algorithm ) OR ( java implication based algorithm ))
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New heuristic function in ant colony system for the travelling salesman problem
Published 2012“…Ant Colony System (ACS) is one of the best algorithms to solve NP-hard problems.However, ACS suffers from pheromone stagnation problem when all ants converge quickly on one sub-optimal solution.ACS algorithm utilizes the value between nodes as heuristic values to calculate the probability of choosing the next node. …”
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Sizing algorithm for stand-alone AC coupled Hybrid PV-diesel power system under Malaysian climate / Nor Syafiqah Syahirah Mohamed
Published 2016“…The sizing algorithm for AC Coupled Hybrid PV-Diesel power system based on Malaysia climate is presented. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…This model is expected to make a significant contribution to the literature of integrated AI-based approach for classification of ACS with high accuracy and efficiency.…”
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Ant Colony Optimization for Solving Solid Waste Collection Scheduling Problems
Published 2009“…But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. …”
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Ant colony optimization for solving solid waste collection scheduling problems
Published 2009“…But the percentage deviations of averages from the associated best cost are 0.1322 and 0.7064 for ACS and SA. The results indicated that for all demand ranges, proposed ACO algorithm showed better performance than SA algorithm. …”
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Short-Term forecasting of floating photovoltaic power generation using machine learning models
Published 2024“…Data were collected at 15-minute intervals from January 15 to January 21, 2024, encompassing nine input features such as ambient temperature, transient horizontal irradiation, daily horizontal irradiation, AC voltages, and AC currents for phases A, B, and C, with the total active power in kW as the target variable. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…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. To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method
Published 2024thesis::doctoral thesis -
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Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen
Published 2023“…This study used a comprehensive methodology to investigate the relationship between air pollution and ACS patient outcomes utilizing machine learning (ML) algorithms, including: 1) Linear Regression, 2) Logistic Regression, 3) Support Vector Machine (SVM), 4) Random Forest (RF), 5) XGBoost, 6) Naïve Bayes (NB), and 7) Stacked Ensemble ML utilizing data from the National Cardiovascular Disease Database (NCVD) Malaysia registry and air quality data from the Department of Environment (DOE) Malaysia. …”
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Advancing agricultural time-series data analysis with a new preprocessing method
Published 2026“…Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) are used to test accuracy, the Seasonality Index (SI) and period-Autocorrelation (AC) are used to measure integrity, and processing time and memory footprints that fit within farm-node limits are used to measure feasibility. …”
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Adopting AHP in evaluating nurse scheduling methods
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