Search Results - (( loading optimization research algorithm ) OR ( variable optimization based algorithm ))

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  1. 1

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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    Thesis
  2. 2

    Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

    Published 2025
    “…Employing both single- and multi-objective optimization algorithms, the research addresses the OPF problem in a modified IEEE-30 bus system through various case studies. …”
    Article
  3. 3

    Optimal parameter estimation of permanent magnet synchronous motor by using Mothflame optimization algorithm / Abdolmajid Dejamkhooy and Sajjad Asefi by Dejamkhooy, Abdolmajid, Asefi, Sajjad

    Published 2018
    “…In the next step, the parameter identification as an optimization problem is solved by Moth-flame optimization, which is a novel nature-inspired heuristic algorithm. …”
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    Article
  4. 4

    Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

    Published 2021
    “…A hybrid population – based stochastic optimization method named MVMO-SH algorithm is proposed to optimize PVDG locations and sizes in the grid system network. …”
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    Thesis
  5. 5

    Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

    Published 2015
    “…A hybrid approach that combines ANN and an evolutionary optimization technique, genetic algorithm (GA) is used for the development of a short term load forecast (STLF) model. …”
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    Article
  6. 6

    To develop an efficient variable speed compressor motor system by Mohd. Yatim, Abdul Halim, Mulyo Utomo, Wahyu

    Published 2007
    “…To achieve a robust controller from variation of motor parameters, a real-time or on-line learning algorithm based on a second order optimization Levenberg-Marquardt is employed. …”
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    Other
  7. 7

    A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization by Jamal S., Pasupuleti J., Ekanayake J.

    Published 2025
    “…In addition to that, a Genetic Algorithm (GA)-based optimization system and Simulated Annealing optimization Algorithm (SAA) were proposed to determine an economical solution for decreasing the cost of the NG system depending on its operational constraints. …”
    Article
  8. 8

    Capacity Planning For Mixed-Load Tester Under Demand And Testing Time Uncertainty by Asih, Hayati Mukti

    Published 2018
    “…Capacity planning is an important decision in production planning as it determines the capacity to install in order to satisfy customer demands and also to allocate products to those capacities.This research is based on mixed-load machine problem which is categorized by multiple products that can be processed simultaneously with different processing time.The problem is further complicated with high product varieties and high demand variabilities.This research was conducted based on a case company from a multinational manufacturing company in Malaysia that produces hard disk drives.The study focused on the automated testing process characterized by long lead time and high product variability.Each testing machine with 2880 slots is a mixed load tester with the ability to load and test multiple product families simultaneously.In addition,the uncertain demand and testing time makes the problem more challenging. …”
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    Thesis
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  10. 10

    Vehicle Routing Problem with Simultaneous Pickup and Delivery by Sze, San Nah, Sek, Siaw Ying Doreen, Sze, Jeeu Fong, Cheah, Wai Shiang, Chiew, Kang Leng

    Published 2020
    “…The considerable data size has increased the difficulty for it to be solved by using mathematical programming or combinatorial optimization. A heuristic approach based on the Variable Neighborhood Search (VNS) is proposed. …”
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    Article
  11. 11

    Interference avoidance routing and scheduling using multiple transceivers for IEEE 802.16 mesh network by Qasem, Yaaqob Ali Ahmed

    Published 2010
    “…This algorithm looks for a short path from the subscriber station (SS) node to BS, while the optimal path is achieved when the whole path has the lowest EbMR. …”
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    Thesis
  12. 12

    Modeling and Optimization of Tapered Rectangular Thin-walled Columns Subjected to Oblique Loading for Impact Energy Absorption by Siti Aishah, Rusdan, Tarlochan, Faris, Mohamad Rusydi, Mohamad Yasin

    Published 2013
    “…The optimal design is obtained by using the constrained nonlinear multivariable optimization algorithm provided by MATLAB. …”
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    Conference or Workshop Item
  13. 13

    New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams by Immad , Shams

    Published 2022
    “…In this work, different areas have been identified, considering both approaches, on which further research has been carried out. In terms of controller-based, in this work, a new global maximum power point tracking (GMPPT) algorithm based on a modified butterfly optimization algorithm (MBOA) has been proposed. …”
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    Thesis
  14. 14

    Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market by Pourdaryaei, Alireza, Mokhlis, Hazlie, Illias, Hazlee Azil, Kaboli, S. Hr. Aghay, Ahmad, Shameem, Ang, Swee Peng

    Published 2019
    “…The unstable nature of electricity price compared to load series causes lower accuracy. Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). …”
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    Article
  15. 15

    Constant lock circuit for DC micro-grid system by Mohammed, Asaad Abduljabbar

    Published 2017
    “…Therefore, this thesis develops DC micro-grid control strategies based on providing continuous load power regardless of the generated power and load demand. …”
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    Thesis
  16. 16

    Online auto-tuned proportional-integral controller using particle swarm optimization for dual active bridge DC-DC converter by Suliana, Ab Ghani

    Published 2021
    “…APSO-PI is an auto-tuned PI using the PSO algorithm where the optimal values of Kp and Kiwere tuned at the initial control process only. …”
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    Thesis
  17. 17

    Review on computational strategies for bi-layered metal powder compaction by Mohd Tahir, Suraya, Mohd Yusoff, Syamimi, Mohamed Ariff, Azmah Hanim, Supeni, Eris Elliandy, Anuar, Mohd Shamsul

    Published 2024
    “…A scrutinize part is the implementation of algorithm to describe powder behavior under double loading as well as to relate with other mechanical variables that eventually require expertise on computational plasticity knowledges involving horizontal contacts. …”
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    Book Section
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  19. 19

    Quantum Particle Swarm Optimization Technique for Load Balancing in Cloud Computing by Elrasheed Ismail, Sultan

    Published 2013
    “…The choice of a scheduling strategy has significant impact on the runtime Central Processing Unit, memory consumption as well as the storage systems. Load balancing optimization techniques such as Ant Colony Optimization (ACO), First Come First Served (FCFS), Round Robin (RR) and Particle Swarm Optimization (PSO) are popular techniques being used for scheduling and load balancing. …”
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    Thesis
  20. 20

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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    Article