Search Results - (( developing data acs algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Attitude Control System for InnoSAT
Published 2009“…To develop attitude control algorithms software; ACS is the part of the ADCS payload. …”
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Embedding Malaysian House Red Ant Behavior into an Ant Colony System
Published 2008“…This research aims to improve the algorithm by embedding individual Malaysian House Red Ant behavior into ACS. …”
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Missing tags detection algorithm for radio frequency identification (RFID) data stream
Published 2019“…AC complement algorithm was used to compare the different in each set of data. …”
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Thesis -
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Improvement DACS3 Searching Performance using Local Search
Published 2009“…Several versions of metaheuristic ACOs’ have been developed through several improvement processes to produce better algorithm. …”
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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 performance indices are used part of the proposed algorithm as a predictive analytical tool for algorithm development. …”
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Improved Dynamic Ant Colony System (DACS) on Symmetric Traveling Salesman Problem (TSP).
Published 2007“…Their ability as a colony to find paths or routes to the food sources has inspired the development of an algorithm namely Ant Colony System (ACS). …”
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Development of a Sensor to Detect Condensation of Super-Sonic Steam
Published 2013“…Time for the AC signals starts form 20 msecond to 1 second. Data acquisition system is employed against each time interval and the output data is fed into EIDORS (a free software algorithm). …”
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Advanced data mining techniques for landslide susceptibility mapping
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A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus
Published 2023“…At this stage, the hybrid EPDEA was selected to be used in the system as it was the best optimization in the hybridization method. All data were then compared to the predicted data that have been developed in the training process, leading to the identification of possible fault in the system. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…Accordingly, the present study attempts to introduce a novel hybrid classification model for the prediction of ACS to fill the multi-stages gaps. To this end, as the initial stage, the pros and cons of the “single AI-based” were evaluated toward providing a strategy in development of the best classification models for prediction of heart failure based on the Perth data set. …”
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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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Predicting the onset of acute coronary syndrome events and in-hospital mortality using machine learning approaches / Song Cheen
Published 2023“…The ML models for regression and classification were developed and optimized; the regression models aimed to predict ACS patients’ hospitalization and mortality rates, while the classification models were designed to predict the mortality risk of ACS patients under the influence of air pollution. …”
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