Search Results - (( using optimization window algorithm ) OR ( using selection method algorithm ))

Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. Three LIRP models involving multiple distribution centers and periods are proposed. …”
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Enhanced AI-based anomaly detection method in the intrusion detection system (IDS) / Kayvan Atefi by Atefi, Kayvan

“…In fact a data clustering method is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on our proposed algorithm; which is Enhanced Binary Particle swarm Optimization (EBPSO), (ii) To mine data using various data chunks (windows) and overcome a failure of single clustering. …”
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Fair bandwidth distribution marking and scheduling algorithm in network traffic classification by Al-Kharasani, Ameen Mohammed Abdulkarem

“…Second, an Optimized time sliding window packet marker (OTSWTCM) algorithm. …”
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Random subspace K-NN based ensemble classifier for driver fatigue detection utilizing selected EEG channels by Rashid, Mamunur, Mahfuzah, Mustafa, Norizam, Sulaiman, Nor Rul Hasma, Abdullah, Rosdiyana, Samad

“…An optimal channel selection approach and a competent classification algorithm might be viewed as a critical aspect of efficient fatigue detection by the driver. …”
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Stereo Matching Based On Absolute Differences For Multiple Objects Detection by Hamzah, Rostam Affendi, Gan, Melvin Yeou Wei, Nik Anwar, Nik Syahrim

“…This article presents a new algorithm for object detection using stereo camera system. …”
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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Optimized crossover genetic algorithm for vehicle routing problem with time windows by Nazif, Habibeh, Lee, Lai Soon

“…Conclusion/Recommendations: This study presented a genetic algorithm for solving vehicle routing problem with time windows using an optimized crossover operator. …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows by Zakaria, M.N.

“…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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Solving multi-objective dynamic vehicle routing problem with time windows using multi-objective algorithm by Khoo, Thau Soon

“…Our algorithm uses non-fitness evolutionary distributed parallelized adaptive large neighbourhood search (NEDPALNS). …”
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Stochastic partially optimized cyclic shift crossover for multi-objective genetic algorithms for the vehicle routing problem with time-windows by Pierre, D.M., Zakaria, N.

“…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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An optimized aggregate marker algorithm for bandwidth fairness improvement in classifying traffic networks by Al-Kharasani, Ameen Mohammed Abdulkarem, Othman, Mohamed, Abdullah, Azizol, Kweh, Yeah Lun

“…This article analyses and evaluates a new time sliding window traffic marker algorithm called the Optimized time sliding window Three Colour Marker (OtswTCM). …”
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Enhancement on the modified artificial bee colony algorithm to optimize the vehicle routing problem with time windows by Sankor, Salah Mortada Shahen

“…The proposed algorithm was evaluated using benchmark datasets comprising 56 VRPTW instances and 56 Pickup and Delivery Problems with Time Windows (PDPTW). …”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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Simulation for dynamic patients scheduling based on many objective optimization and coordinator by Mahmed, Ali Nader, Mohd Nizam, Mohmad Kahar

“…Finally, the role of the coordinator is to select a subset of patients from the window and pass them to the optimization algorithm. …”
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Removal of high density salt and pepper noise from image and video based on optimal decision based algorithm by Khammar, Mohammad Reza, Saripan, M. Iqbal, Marhaban, Mohammad Hamiruce, Ishak, Asnor Juraiza

“…Detection is provided by using statistical analysis in each window, then the appropriate replacement for the noisy pixel is conducted from given values inside the current window or adjacent reconstructed pixels based on mean calculation and also, for very high density of noise which density of noise is bigger than 80%, the reconstruction is based on a recursive approach. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm by Abubakar, Adamu, Chiroma, Haruna, Khan, Abdullah, Mohamed, Elbaraa Eldaw Elnour

“…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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Single Step Multivariate Solar Power Forecasting using Adaptive Learning Rate LSTM Model with Optimized Window Size by Kunalan D., Krishnan P.S., Permal N.

Configuration and analysis of piezoelectric-based in socket sensory system for transfemoral prosthetic Gait detection / Farahiyah Jasni by Farahiyah , Jasni

“…The methodology comprised of selecting: (a) the best piezoelectric sensor to be used in terms of the material, size and shape, (b) the method of mounting the sensors onto the socket, and (c) the placement of the sensors. …”
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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks by Muftah, Shalghum Khaled

“…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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Network calculus-based latency for time-triggered traffic under Flexible Window-Overlapping Scheduling (FWOS) in a Time-Sensitive Network (TSN) by Shalghum, Khaled M., Noordin, Nor Kamariah, Sali, Aduwati, Hashim, Fazirulhisyam

“…Accordingly, more relaxed scheduling algorithms are required. In this paper, we introduce the flexible window-overlapping scheduling (FWOS) algorithm that optimizes the overlapping among TT windows by three different metrics: the priority of overlapping, the position of overlapping, and the overlapping ratio (OR). …”
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