Search Results - (( intelligence based gene algorithm ) OR ( intelligence based a algorithm ))

VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS. by FAROOQ, HUMERA

“…The aim of the proposed approach is to study the benefit of using visualization techniques to explorer Genetic Algorithm data based on gene values. The user participates in the search by proposing a new individual. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…Then, in order to cope with the limitations of the existing artificial intelligence (AI) based methods, optimized gene expression programming (GEP) is applied to precisely formulate the relationships between historical data and EEC of ASEAN-5 countries. …”
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The development of semantic meta-database: an ontology based semantic integration of biological databases by Samsudin, Ruhaidah, Deris, Safaai, Othman, Muhammad Razib, Md. Illias, Rosli

“…The tool comprises two intelligent algorithms. The first algorithm combines parallel genetic algorithm with the split-and-merge algorithm. …”
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Incorporating semantic similarity measure in genetic algorithm: an approach for searching the gene ontology terms by M. Othman, Razib, Deris, Safaai, M. Ilias, Rosli, Alashwal, Hany Taher Ahmed, Hassan, Rohayanti, Mohamed, Farhan

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Industry 4.0 With Intelligent Manufacturing 5G Mobile Robot Based On Genetic Algorithm by Anwar Apandi, Nur Ilyana, Hawari, Mohd Zarifitri Kasim

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An Evaluation of Machine Learning Algorithms for Missing Values Imputation by Kohbalan, Moorthy, Ali, Mohammed Hasan, Mohd Arfian, Ismail, Chan, Weng Howe, Mohd Saberi, Mohamad, Safaai, Deris

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Optic cup and optic disc segmentation using improved selfish gene algorithm / Norharyati Md Ariff by Md Ariff, Norharyati

“…This study performed using a new bio-inspired algorithm; Selfish Gene Algorithm (SFGA) for optic cup and optic disc segmentation. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

“…Immune based algorithm is part of bio-inspired algorithms elicits theories which can act as an inspiration for computer-based solutions. …”
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Exploring the High Performance Computing-Enablement of a Suite of Gene-Knockout Based Genetic Engineering Applications by Li, Zhenya, Sinnott, Richard O., Choon, Yee Wen, Sjaugi, Muhammad Farhan, Mohd Saberi, Mohamad, Safaai, Deris, Suhaimi, Napis, Omatu, Sigeru, Corchado, Juan Manuel, Zuwairie, Ibrahim, Zulkifli, Md. Yusof

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A hybrid of ant colony optimization, genetic algorithm and flux balance analysis for optimization of succinic acid production in Escherichia coli by Tan, Jun Bin, Choon, Yee Wen, Moorthy, Kohbalan, Hasyiya Karimah, Adli, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Zuwairie, Ibrahim, Mohd Saberi, Mohamad

“…Ant colony optimization (ACO) is a swarm intelligent optimization that is inspired based on the natural foraging behavior of ant colony. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Overview of biomedical relations extraction using hybrid rule-based approaches. by Abdul Kadir, Rabiah, Bokharaeian, Behrouz

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Deriving the absorption coefficients of lattice mismatched InGaAs using genetic algorithm by Lee H.J., Ali Gamel M.M., Ker P.J., Jamaludin M.Z., Wong Y.H., Yap K.S., Willmott J.R., Hobbs M.J., David J.P.R., Tan C.H.

“…By selecting the best gene for the next iteration, the utilization of Genetic Algorithm has significantly reduced the number of iterations from a maximum of 10 000 to 300. …”

Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line by Noroziroshan, Alireza, Mohd Ariffin, Mohd Khairol Anuar, Ismail, Napsiah

“…A heuristic algorithm was introduced to generate the initial population for intelligence based genetic algorithm. …”
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Active intelligent control of vibration of flexible plate structures by Md Salleh, Salihatun

“…In this work active intelligent control comprises a set of control techniques based on particle swarm optimisation (PSO), real coded genetic algorithm (RCGA) and artificial immune system (AIS). …”
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A Comparative Study of the Application of Swarm Intelligence in Kruppa-Based Camera Auto-Calibration by Jaafar, Hazriq Izzuan

“…This paper presented a comparative study of the application of two Swarm Intelligence algorithms: Particle Swarm Optimization and Firefly Algorithm in automatic camera calibration problem. …”
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Hybrid Intelligent Water Drops Algorithm For Examination Timetabling Problem by Bashar A.Aldeeb, Mohammed Azmi Al-Betar, Norita Md Norwawi, Khalid A.Alissa, Mutasem K.Alsmadi, Ayman A.Hazaymeh, Malek Alzaqebah

Solving university examination timetabling problem using intelligent water drops algorithm by Aldeeb B.A., Norwawi N.M., Al-Betar M.A., Jali M.Z.B.

A Theoretical Framework for Big Data Analytics Based on Computational Intelligent Algorithms with the Potential to Reduce Energy Consumption by Chiroma, H., Abdullahi, U.A., Hashem, I.A.T., Saadi, Y., Al-Dabbagh, R.D., Ahmad, M.M., Dada, G.E., Danjuma, S., Maitama, J.Z., Abubakar, A., Abdulhamid, S.�M.

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Intelligent examination timetabling system using hybrid intelligent water drops algorithm by AlDeeb, Bashar A., Md Norwawi, Norita, Al-Betar, Mohammed A., Jali, Mohd Z.

“…This paper proposes Hybrid Intelligent Water Drops (HIWD) algorithm to solve Tamhidi programs uncapacitated examination timetabling problem in Universiti Sains Islamic Malaysia (USIM).Intelligent Water Drops algorithm (IWD) is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to better drops.The results of this study prove that the proposed algorithm can produce a high quality examination timetable in shorter time in comparison with the manual timetable.…”
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