Search Results - (( parameter information scheduling algorithm ) OR ( java application optimisation algorithm ))

Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm by Muthana, Shatha Abdulhadi, Ku Mahamud, Ku Ruhana

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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Meta-scheduler in Grid environment with multiple objectives by using genetic algorithm by Lorpunmanee, Siriluck, Sap, M.N.M, Abdullah, Abdul Hanan, Srinoy, Surat

“…The simulation has been obtained using historical information to study the job scheduling in Grid environment. …”
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The comparison of tardiness in scheduling techniques for task distribution using grid simulation tool by Stapa @ Mustapa, Muhamad Azhar

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Strategic oscillation for exploitation and exploration of ACS algorithm for job scheduling in static grid computing by Alobaedy, Mustafa Muwafak, Ku-Mahamud, Ku Ruhana

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Tasks Distribution In Driver Scheduling Using Dynamic Set Of Bandwidth In Harmony Search Algorithm With 2-Opt by Shaffiei, Zatul Alwani

“…Therefore, a tasks distribution in driver scheduling using dynamic set of bandwidth in harmony search algorithm with 2-opt (SBHS2-opt) was proposed in this research. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…In addition, the marking probability mechanism was studied to check how the parameters in the traffic rate affect fairness. Additionally, the traffic are relying on the markers and scheduling algorithms to the service classes at the routers. …”
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Improvement of Centralized Routing and Scheduling Using Cross-Layer Design and Multi-Slot Assignment in Wimax Mesh Networks by Al-Humairi, Ali Zuhair Abdulameer

“…This thesis proposes an optimized strategy namely cross-layer design in routing algorithms used find the best route for all SSs and scheduling algorithms, used to assign a time slot for each possible node transmission. …”
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A review energy-efficient task scheduling algorithms in cloud computing by Atiewi S., Yussof S., Ezanee M., Almiani M.

Two-level QoS-oriented downlink packet schedulers in LTE networks: a review by Ferdosian, Nasim, Othman, Mohamed

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Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review by Uddin, Mueen, Darabidarabkhani, Yasaman, Shah, Asadullah, Memon, Jamshed

“…CloudSim simulator is used to implement the algorithms on an IaaS cloud infrastructure, to calculate the power consumption, and to analyze each algorithm's behavior for different parameters. …”
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A predictive approach to improve a fault tolerance confidence level on grid resources scheduling by Bouyer, Asgarali, Md. Sap, Mohd. Noor

“…Many methods are presented in a few years ago, but in these algorithms, some parameters such as job requirements and clear predictor method are not truly considered and also some methods apply optimistic view in grid scheduling cycle. …”
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Network Capacity Issues in Joint Buffer Management and Scheduling (JoBS) by Nur Idawati Md Enzai, Hasnorhafiza Husni, Siti Sara Rais, Nor Raihan Zulkefly

Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems by Salman, Mustafa Ismael

“…Specifically, the downlink frequency domain scheduler will reconfigure the criteria priorities such that the EE is maximized as long as the QoS is guaranteed.On the other hand, the partial feedback algorithm will search for the threshold value that minimizes the uplink overhead given that the QoS is achieved at the downlink.Otherwise, optimizing QoS parameters will be targeted at the cost of other system parameters. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil by Jamli, Mohd Radhi Fauzan, Ahmad Fadzil, Ahmad Firdaus

“…Extensive experimentation with genetic algorithm parameters has yielded promising results, notably a parameter set (population size = 12, generation size = 30, mutation rate = 0.2) demonstrating robust performance, achieving optimal timetables with swift convergence and minimal conflicts. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

“…These values are used to define the objective function’s parameters. Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. …”
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Time division multiple access-based scheduling algorithm for quality of service enhancement in IEEE 802.11s wireless mesh networks by Mohammed, Abdulnasser Ahmed

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Intelligent optimization for charging scheduling of electric vehicle using exponential Harris Hawks technique by Devendiran R., Kasinathan P., Ramachandaramurthy V.K., Subramaniam U., Govindarajan U., Fernando X.

Adaptive multi-polling scheduler for QoS support of video transmission in IEEE 802.11e WLANs by Al-Maqri, Mohammed A., Othman, Mohamed, Mohd Ali, Borhanuddin, Mohd Hanapi, Zurina

“…In this paper, we present a dynamic TXOP assignment algorithm called adaptive multi-polling TXOP scheduling algorithm (AMTXOP) for supporting the video traffics transmission over IEEE 802.11e wireless networks. …”
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Motion planning and control for autonomous vehicle collision avoidance systems using potential field-based parameter scheduling by Nurbaiti, Wahid, Hairi, Zamzuri, Noor Hafizah, Amer, Dwijotomo, Abdurahman, Sarah ‘Atifah, Saruchi

“…This study proposed a motion planning and control strategy for an autonomous vehicle collision avoidance system based on the potential field (PF) approach with a combination of the parameter scheduling technique. A particle swarm optimization algorithm is used to optimize the knowledge database information that is developed based on the perception of driver toward risk in the driving environment. …”
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