Search Results - (( java implementation towards algorithm ) OR ( framework implementation modified algorithm ))
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Implementation of locust inspired scheduling algorithm with huge number of servers for energy efficiency in a cloud datacenter
Published 2019“…It does not consider the LACE algorithm implemented in huge number of server in one Cloud datacenter. …”
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Thesis -
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Network game (Literati) / Chung Mei Kuen
Published 2003“…This thesis steps towards developing a networked game, Literati game system that supporting two players at one time. …”
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A modified genetic algorithm for controller placement problem in SDN distributed network
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Conference or Workshop Item -
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Two modified genetic algorithms are devised and employed to provide the best approximate process planning solution. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…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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Modified quasi-Newton type methods using gradient flow system for solving unconstrained optimization
Published 2016“…We also implement the Newton-type methods on trust region framework by using unit step length to adjust the radius of the region to obtain desired reduction in the objective function. …”
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9
Modelling Autonomous Evacuation Navigation System (AENS) for optimal route using Dijkstra's algorithm
Published 2016“…Through ST adaptation, all subsystems were integrated and using the “Dijkstra’s algorithm” (DA) by modifying its function from shortest path algorithm to safest and shortest algorithm, to the nearest exit. …”
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Smart grid: Bio-inspired algorithms energy distributions for data centers
Published 2025“…The system is implemented and simulated using the CloudSim Plus framework under both homogeneous and heterogeneous data centre environments. …”
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Final Year Project / Dissertation / Thesis -
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Runtime pluggable CPU scheduler for linux operating system
Published 2010“…It added more flexibility to the Linux CPU heduler. It has been implemented in three layers, kernel, modules, and user interface layer, to simplify the framework development and maintenance as well as to maintain performance. …”
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13
Review of the grey wolf optimization algorithm: variants and applications
Published 2023“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…The study's trajectory takes a subtle turn as it proposes a modified methodology that includes a detailed comparison investigation of several line search strategies inside the SD algorithm. …”
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Student Project -
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement
Published 2023“…Therefore, the proposed framework is proven to be competitive with other established methods and can be used as a complete algorithm.…”
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17
Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…Deep neural networks (DNNs) are very dependent on their parameterization and require experts to determine which method to implement and modify the hyper-parameters value. This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…The circuits have been designed by proteus, the microcontrollers have been programmed by micro C, and the Graphical User Interface (GUI) has been implemented in Java. Few by electronic components such as RFID, multiplexer, XBee, and servo motors have been used to realize the system. …”
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A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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20
Review of the grey wolf optimization algorithm: variants and applications
Published 2024“…The paper begins with a concise introduction to the GWO, providing insight into its natural establishment and conceptual framework for optimization. It then lays out the theoretical foundation and key procedures involved in the GWO, following which it comprehensively examines the most recent iterations of the algorithm and categorizes them into parallel, modified, and hybridized variations. …”
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