Search Results - (( model validation bees algorithm ) OR ( based construction phase algorithm ))*

Bee colony optimisation of the travelling salesman problem in light rail systems by Wang, Chen, Leong, Kah Huo, Abdul-Rahman, Hamzah

“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months by Suarin, Nur Aisyah Syafinaz, Chia, Kim Seng, Mohamad Fuzi, Siti Fatimah Zaharah

“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly by Zulkifly, Ahmad Zuladzlan

“…The study on related work and comparison of algorithm also has been done in this phase. In Design phase, the use case diagram, whole system flowchart and subsystem flowchart has been constructed to assist the development of this web tool. …”
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A hybrid adaptive harmony search with modified great deluge algorithm for school timetabling by Arbaoui, Billel

“…This research enhances HSA by hybridizing it with the Great Deluge Algorithm (GDA) using a four-phase methodology. In Phase 1, heuristic rules refine the time assignment stage to improve an existing construction algorithm. …”
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Design and statistical analysis of initial solution construction approach in curriculum based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…This paper investigates the construction phase approach in which the sequential order of the courses/lectures applied several combination of graph heuristics to generate a population of initial solutions in curriculum-based course timetabling (CBCTT).The construction of population of initial solution is a prerequisite in a population-based metaheuristic implementation. …”
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Enhanced ABD-LSSVM for energy fuel price prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…This paper presents an enhanced Artificial Bee Colony (eABC)based on Lévy Probability Distribution (LPD) and conventional mutation. …”
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Constructing population of initial solutions for curriculum – based course timetabling problem by Wahid, Juliana, Mohd Hussin, Naimah

“…Future work will use the best settings of heuristics to the improvement phase in population-based improvement algorithm.…”
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Enhancing the Sorting Layers in the Initial Stage of High School Timetabling by Arbaoui, Billel, Wahid, Juliana, Abdul-Rahman, Syariza

“…The high school timetabling problem (HSTP) is considered as an NP-Complete problem as the optimal solution for it, is still not discovered by any algorithm. Generally, NP-Complete problem was solved firstly by constructing the initial solution, in the construction phase. …”
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Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming by Altahir, A.A., Asirvadam, V.S., Hamid, N.H.B., Sebastian, P., Saad, N.B., Ibrahim, R.B., Dass, S.C.

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A Distributed Energy Aware Connected Dominating Set Technique for Wireless Sensor Networks by Abd Aziz, Azrina, Sekercioglu, Ahmet

“…Our algorithm, a single-phase single initiator (SPSI), only requires a single phase to construct a CDS in a distributed manner using localized information. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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Enhanced ABC-LSSVM For Energy Fuel Price Prediction by Mustaffa, Zuriani, Yusof, Yuhanis, Kamaruddin, Siti Sakira

“…To evaluate the effi ciency of the proposed model, crude oil prices data was employed as empirical data and a comparison against four approaches were conducted, which include standard ABC-LSSVM, Genetic Algorithm-LSSVM (GA-LSSVM), Cross Validation-LSSVM (CV-LSSVM), and conventional Back Propagation Neural Network (BPNN). …”
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Automated Examination Timetabling System (AETSys) / Ariff Md Ab Malik by Md Ab Malik, Ariff, Haruddin, Hanitahaiza, Alwi, Anisah, Mohamed, Khainizam

“…This system has been developed based on a hybridization of local search-population based metaheuristic algorithms. …”
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Modified anfis architecture with less computational complexities for classification problems by Talpur, Noureen

“…The proposed ANFIS model is trained by one of the metaheuristics approach instead of standard two pass learning algorithm. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

CPLD based controller for single phase inverters by Saiman, Suhaimi

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CPLD based controller for single phase inverters by Saiman, Suhaimi

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SVM for network anomaly detection using ACO feature subset by Mehmood, T., Rais, H.B.M.

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