Search Results - (( based optimization window algorithm ) OR ( pattern extraction bees algorithm ))
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows
Published 2017“…This paper presents a stochastic partially optimized cyclic shift crossover operator for the optimization of the multi-objective vehicle routing problem with time windows using genetic algorithms. …”
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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
Published 2015“…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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Proceeding Paper -
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm
Published 2014“…This paper proposes an optimal method to suppress the noise with high density properly based on a nonlinear filter and decision-based approach. …”
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Conference or Workshop Item -
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator
Published 2024“…Taking both aspects, optimization and dynamic utilization, we propose a simulation for dynamic patient scheduling based on multi-objective optimization, window, and coordinator. …”
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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
Published 2015“…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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Book Chapter -
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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks
Published 2022“…The second part proposes an optimized flexible window-overlapping scheduling (OFWOS) algorithm that optimizes the offset difference ( ) between the samepriority TT windows in the adjacent nodes. …”
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Enhanced local disparity map algorithm segment-side window-based cost aggregation and refinement
Published 2025“…This paper introduces a Segment-Side Window based (SSW) stereo matching algorithm that combines Truncated Absolute Difference (TAD), Gradient Magnitude (GM), and Census Transform (CT) to build a robust cost volume. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…This signifies that the training was successful based on the fitted values of the window size. Thus the proposed model trained with the CS algorithm provides a high convergence rate to the true global minimum and a better optimal solution. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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Thesis -
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification
Published 2019“…Second, propose an Optimized Time Sliding Window based Three Colour Marker. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Conference or Workshop Item -
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Local Stereo Matching Algorithm Using Small-Color Census Spared Adaptive Support Weight
Published 2011“…This work is still on process, to test the algorithm; it will use the Middlebury benchmark. According to analysis of each step of the algorithms, the proposed SCCADSW can achieve good performance among stereo methods that rely on local optimization…”
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Conference or Workshop Item -
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Worst-case latency analysis for AVB traffic under overlapping-based time-triggered windows in time-sensitive networks
Published 2022“…In this paper, a worst-case end-to-end delay (WCD) for AVB traffic under overlapping-based TT windows (AVB-OBTTW) algorithm is proposed. …”
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