Search Results - (( using computing bees algorithm ) OR ( simulation optimization method algorithm ))

Search alternatives:

Refine Results
  1. 1
    System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm

    System performances analysis of reservoir optimization�simulation model in application of artificial bee colony algorithm by Hossain M.S., El-Shafie A., Mahzabin M.S., Zawawi M.H.

    Published 2023
    Article
    Save to List
    Saved in:
  2. 2
    A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli

    A hybrid of Simple Constrained artificial bee colony algorithm and flux balance analysis for enhancing Lactate and Succinate in Escherichia Coli by Hon, Mei Kie, Mohd Saberi, Mohamad, Abdul Hakim, Mohamed Salleh, Choon, Yee Wen, Muhammad Akmal, Remli, Mohd Arfian, Ismail, Omatu, Sigeru, Corchado, Juan Manuel

    Published 2018
    “…The hybrid algorithm employed the Simple Constrained Artificial Bee Colony (SCABC) algorithm, using swarm intelligence as an optimization algorithm to optimize the objective function, where lactate and succinate productions are maximized by simulating gene knockout in E. coli. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Book Chapter
    Save to List
    Saved in:
  3. 3
    System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm

    System performances analysis of reservoir optimization–simulation model in application of artificial bee colony algorithm by Hossain, Md Shabbir, El-Shafie, Ahmed, Mahzabin, Mst Sadia, Zawawi, Mohd Hafiz

    Published 2018
    “…Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are also used in a view of comparing model performances. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  4. 4
    Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony

    Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony by Mohd Izuddin Sipluk

    Published 2022
    “…During the methodology chapter, a comprehensive investigation has been done to ascertain the proposed method that can be adopted such as algorithms involved, project flow, and simulation. …”
    Get full text
    Get full text
    Get full text
    Academic Exercise
    Save to List
    Saved in:
  5. 5
    Improved cuckoo search based neural network learning algorithms for data classification

    Improved cuckoo search based neural network learning algorithms for data classification by Abdullah, Abdullah

    Published 2014
    “…This research proposed an improved CS called hybrid Accelerated Cuckoo Particle Swarm Optimization algorithm (HACPSO) with Accelerated particle Swarm Optimization (APSO) algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  6. 6
    Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms

    Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms by Mohammadi, M., Musa, S.N., Bahreininejad, A.

    Published 2015
    “…The computational performance and statistical optimization results show the effectiveness and superiority of the metaheuristic algorithms over other reported methods in the literature. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  7. 7
    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification

    Weight Optimization in Recurrent Neural Networks with Hybrid Metaheuristic Cuckoo Search Techniques for Data Classification by Nawi, N.M., Khan, A., Rehman, M.Z., Chiroma, H., Herawan, T.

    Published 2015
    “…The proposed CSERN and CSBPERN algorithms are compared with artificial bee colony using BP algorithm and other hybrid variants algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  8. 8
    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  9. 9
    LSSVM parameters tuning with enhanced artificial bee colony

    LSSVM parameters tuning with enhanced artificial bee colony by Mustaffa, Zuriani, Yusof, Yuhanis

    Published 2014
    “…To guarantee its convincing performance, it is crucial to select an appropriate technique in order to obtain the optimized hyper-parameters of LSSVM algorithm.In this paper, an Enhanced Artificial Bee Colony (eABC) is used to obtain the ideal value of LSSVM’s hyper parameters, which are regularization parameter, γ and kernel parameter, σ2.Later, LSSVM is used as the prediction model. …”
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  10. 10
    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman smoother adaptive filter by Yazid, E., Liew, M.S., Parman, S., Kurian, V.J.

    Published 2015
    “…The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  11. 11
    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS

    Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

    Published 2017
    “…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  12. 12
    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  13. 13
    Optimization of neural network using cuckoo search for the classification of diabetes

    Optimization of neural network using cuckoo search for the classification of diabetes by Abubakar, Adamu, Shuib, Liyana, Chiroma, Haruna

    Published 2015
    Get full text
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  14. 14
    A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique

    A stable energy balancing based clustering routing protocol for IoUT using meta-heuristic technique by Ali, Elmustafa Sayed, Saeed, Rashid A, Eltahir, Ibrahim Khider, Khalifa, Othman Omran

    Published 2024
    “…The proposed method enable to optimization the IoUT energy efficiency by balancing strategy that uses the Q-learning algorithm to ensure more balanced distribution of tasks across UNs and CHs. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Proceeding Paper
    Save to List
    Saved in:
  15. 15
    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches

    Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches by Mohd Pauzi, Nur Fazlinda

    Published 2015
    “…The research also analyzes the performance of the ABC algorithm using three different onlooker bee approaches. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
    Save to List
    Saved in:
  16. 16
    Application of the bees algorithm to the selection features for manufacturing data

    Application of the bees algorithm to the selection features for manufacturing data by Pham, D.T, Mahmuddin, Massudi, Otri, S., Al-Jabbouli, H.

    Published 2007
    “…A “wrapper” feature selection method using the Bees Algorithm and Multilayer Perception (MLP) networks is described in this paper. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:
  17. 17
    Autonomous object movement in modeling bees foraging

    Autonomous object movement in modeling bees foraging by Theab, Mustafa Muwafak, Yusof, Yuhanis

    Published 2010
    Get full text
    Get full text
    Get full text
    Book Section
    Save to List
    Saved in:
  18. 18
    Solving the travelling salesman problem by using artificial bee colony algorithm / Siti Hafawati Jamaluddin ... [et al.]

    Solving the travelling salesman problem by using artificial bee colony algorithm / Siti Hafawati Jamaluddin ... [et al.] by Jamaluddin, Siti Hafawati, Mohd Naziri, Noor Ainul Hayati, Mahmud, Norwaziah, Muhammat Pazil, Nur Syuhada

    Published 2022
    Get full text
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  19. 19
    Global gbest guided-artificial bee colony algorithm for numerical function optimization

    Global gbest guided-artificial bee colony algorithm for numerical function optimization by Shah, Habib, Tairan, Nasser, Garg, Harish, Ghazali, Rozaida

    Published 2018
    “…Numerous computational algorithms are used to obtain a high performance in solving mathematics, engineering and statistical complexities. …”
    Get full text
    Get full text
    Article
    Save to List
    Saved in:
  20. 20
    Using the bees algorithm to optimise a support vector machine for wood defect classification

    Using the bees algorithm to optimise a support vector machine for wood defect classification by Pham, D.T, Muhammad, Zaidi, Mahmuddin, Massudi, Ghanbarzadeh, Afshin, Koc, Ebubekir, Otri, Sameh

    Published 2007
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
    Save to List
    Saved in:

Search Tools: