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  1. 1
    Examining performance of aggregation algorithms for neural network-based electricity demand forecasting

    Examining performance of aggregation algorithms for neural network-based electricity demand forecasting by Hassan, S., Khosravi, A., Jaafar, J.

    Published 2015
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  2. 2
    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network

    Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network by Usman, I. H., Nordin, N. K., Omizegba, E. E., Sali, A., Rasid, M. F. A., Hashim, F.

    Published 2021
    “…This implied that the network operating under the proposed TVWS algorithm presented low radio link decoding errors when compared with the validation algorithms MIF and CONV. …”
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  3. 3
    m-polar generalization of fuzzy T-ordering relations: an approach to group decision making

    m-polar generalization of fuzzy T-ordering relations: an approach to group decision making by Khameneh, Azadeh Zahedi, Kilicman, Adem

    Published 2020
    “…Recently, T-orderings, defined based on a t-norm T and infimum operator (for infinite case) or minimum operator (for finite case), have been applied as a generalization of the notion of crisp orderings to fuzzy setting. …”
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  4. 4
    A decomposition/aggregation method for solving electrical power dispatch problems

    A decomposition/aggregation method for solving electrical power dispatch problems by Mansor M.H., Irving M.R., Taylor G.A.

    Published 2023
    “…Subsequently, the solutions from the areas are combined (aggregated) to solve the overall system problem. The results obtained using the decomposition / aggregation method are compared with the results found when the ED Problem was solved using a centralised EP approach and the base-case results found from solving a (non-optimal) load flow. …”
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  5. 5
    Selection of investment company based on interval neutrosophic vague heronian operator

    Selection of investment company based on interval neutrosophic vague heronian operator by Hashim, Hazwani, Awang, Noor Azzah, Mohamad, Siti Nurul Fitriah

    Published 2022
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  6. 6
    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced

    Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced by Ahmed-Abdulazeez, Mariam Ovayioza

    Published 2018
    “…The HHPO and the MC-HOD algorithms achieves significant enhancement compared to the conventional and other algorithms examined. …”
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  7. 7
    A genetic algorithm for solving single level lotsizing problems

    A genetic algorithm for solving single level lotsizing problems by Zenon, Nasaruddin, Ahmad, Ab. Rahman, Ali, Rosmah

    Published 2003
    “…In our implementation, a lot-sizing population-generating heuristic is used to feed chromosomes to a genetic algorithm with operators specially designed for lot-sizing problems. …”
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  8. 8
    Two level aggregation scheme with optimization in subframes headers for IEEE 802.11n wireless networks

    Two level aggregation scheme with optimization in subframes headers for IEEE 802.11n wireless networks by Noma, Adamu Muhammad

    Published 2014
    “…Furthermore, a new two-level aggregation model is developed by integrating the eA-MSDU into A-MPDU and designing suitable operating algorithm. …”
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  9. 9
    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment

    Hybrid meta-heuristic algorithm for solving multi-objective aggregate production planning in fuzzy environment by Kalaf, Kalaf, Bayda Atiya

    Published 2017
    “…Aggregate production planning (APP) is considered as significant for efficient production systems. …”
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  10. 10
    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks

    Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

    Published 2024
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  11. 11
    Octopus++: an enhanced mutual authentication security protocol and lightweight encryption and decryption algorithm based on DNA in fog computing

    Octopus++: an enhanced mutual authentication security protocol and lightweight encryption and decryption algorithm based on DNA in fog computing by Rahman, Gohar

    Published 2023
    “…Next, we proposed a modified security protocol based on ONDNA and hash message authentication code with secure hash algorithm 2. …”
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  12. 12
    Octopus++: an enhanced mutual authentication protocol with lightweight encryption and decryption algorithm based on dna in fog computing

    Octopus++: an enhanced mutual authentication protocol with lightweight encryption and decryption algorithm based on dna in fog computing by Rahman, Gohar

    Published 2023
    “…Next, we proposed a modified security protocol based on ONDNA and hash message authentication code with secure hash algorithm 2. …”
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  13. 13
    Real-time time series error-based data reduction for internet-of-things applications

    Real-time time series error-based data reduction for internet-of-things applications by Wong, Siaw Ling

    Published 2018
    “…There are many time series data reduction methods, ranging from primitive data aggregation such as Rate of Change to sophisticated compression algorithms. …”
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    Final Year Project / Dissertation / Thesis
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  14. 14
    Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm

    Eccentricity Optimization of NGB System by using Multi-Objective Genetic Algorithm by Yazdi, H.M., Ramli Sulong, N.H.

    Published 2009
    “…Boundary equations are set by introducing feasible area to avoid improper individuals followed by utilization of some operators such as selection, mutation, crossover and elite genetic algorithm. …”
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  15. 15
    Normalized advancement based totally opportunistic routing algorithm with void detection and avoiding mechanism for underwater wireless sensor network

    Normalized advancement based totally opportunistic routing algorithm with void detection and avoiding mechanism for underwater wireless sensor network by Rahman, Ziaur, Hashim, Fazirulhisyam, A. Rasid, Mohd Fadlee, Othman, Mohamed, Alezabi, Kamal Ali Ahmed

    Published 2020
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  16. 16
    Prospective Control Systems and Cyber-Securities for Electrical Secondary Substations

    Prospective Control Systems and Cyber-Securities for Electrical Secondary Substations by Jidin R., Basir Khan M.R., Jamil N., Al-Bahadly I.

    Published 2023
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  17. 17
    The implications for ahybrid detection technique against malicious sqlattacks on web applications

    The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

    Published 2025
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  18. 18
    An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information

    An adjustable approach to multi-criteria group decision-making based on a preference relationship under fuzzy soft information by Khameneh, Azadeh Zahedi, Kilicman, Adem, Salleh, Abdul Razak

    Published 2017
    “…To date, different algorithms have been proposed for solving collective decision-making problems based on fuzzy soft set theory. …”
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  19. 19
    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming

    An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming by Mohamad Ridzuan, Mohamad Radzi

    Published 2018
    “…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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  20. 20
    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution

    Solving vehicle routing problem by using improved K-nearest neighbor algorithm for best solution by Mohammed, Mazin Abed, Abd Ghani, Mohd Khanapi, Hamed, Raed Ibraheem, A. Mostafa, Salama, Ahmed Ibrahim, Dheyaa, Jameel, Humam Khaled, Alallah, Ahmed Hamed

    Published 2017
    “…Approach: The approach has been presented based on two phases: firstly, the algorithms have been adapted to solve the research problem, where its procedure is different than the common algorithm. …”
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