Search Results - (( sequence optimization method algorithm ) OR ( sequence optimization means algorithm ))*

Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment by Ibrahim, Al-Zaidi Mohammed Khaleel

“…A notable entrant in this domain is the harris hawks optimization (hho) algorithm, which has distinguished itself through published optimization outcomes, positioning it as a formidable competitor among state-of-the-art metaheuristics. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…These two models are based on topological placement method. DM is optimized using genetic algorithm (GA). …”
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Development of multi-objective optimization methods for integrated scheduling of handling equipment (AGVs, QCs, SP-AS/RS) in automated container terminals by Homayouni, Seyed Mahdi

“…Therefore, two meta-heuristic algorithms, namely genetic algorithm (GA) and simulated annealing (SA) algorithm, were developed to optimize the integrated scheduling of handling equipment. …”
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Optimization of Simultaneous Scheduling for Machines and Automated Guided Vehicles Using Fuzzy Genetic Algorithm by Badakhshian, Mostafa

“…An optimal sequence of operations is obtained by GA. …”
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Technical report: genetic algorithm for vehicle routing problem / Mohammad Izwan Jamaluddin and Muhamad Syahmie Adeeb Mohd Shukri by Jamaluddin, Mohammad Izwan, Mohd Shukri, Muhamad Syahmie Adeeb

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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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A genetic algorithm to minimise the maximum lateness on a single machine family scheduling problem by Lee, Lai Soon, Nazif, Habibeh

“…The OCGA is compared with other well known local search method namely dynamic length tabu search, randomised steepest descent method, and other variants of genetic algorithms using extensive data sets collected from the literatures. …”
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Estimation of Transformers Health Index Based on Condition Parameter Factor and Hidden Markov Model by Selva A.M., Yahaya M.S., Azis N., Ab Kadir M.Z.A., Jasni J., Yang Ghazali Y.Z.

Weather Prediction for Strawberry Cultivation Using Double Exponential Smoothing and Golden Section Optimization Methods by Herlinah, Asrul, Billy Eden William, Hafsah, Faisal, Muhammad, Lee Lee, Swa, Gani, Hamdan, Feng, Zhipeng

“…The algorithm used to predict the air temperature feature, wind speed feature, and rainfall feature was Double Exponential Smoothing, followed by the optimization of the Golden Section method to select the right smoothing value. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

“…The results demonstrate that the proposed optimal maintenance scheduling method yields much better system value rather than sequencing methods. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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Neural network-based codebook search for image compression by Bodruzzaman, M., Gupta, R., Karim, M.R., Bodruzzaman, S.

“…The image to be coded is first clustered into a small subset of neighboring images and then the neural network-based encoder is used to find the best matching code sequences in the codebook. This subset is then used as a candidate set and an exhaustive search is then performed within this subset to find an optimal code sequence which minimizes the perceptual error between coded and decoded images. …”
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Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

“…Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. Subsequently, the future states probability distribution was computed based on the HMM prediction model and viterbi algorithm was applied to find the best optimal path sequence of HI for the respective observable condition. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

“…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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Intelligent grading of agarwood essential oil quality using artificial neural network (ANN) / Noratikah Zawani Mahabob by Mahabob, Noratikah Zawani

“…The training and validation of the ANN was based on optimization of its training parameters and guided by the convergence of the mean squared errors (MSE). …”
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A study on component-based technology for development of complex bioinformatics software by Ali Shah, Zuraini, Deris, Safaai, Othman, Muhamad Razib, Zakaria, Zalmiyah, Saad, Puteh, Hassan, Rohayanti, Muda, Mohd. Hilmi, Kasim, Shahreen, Roslan, Rosfuzah

“…Based on the protein sequence datasets obtained from PISCES database, they found iii that the R-HCSVM performs outstanding result in predicting protein local structure from a given protein subsequence compared to other methods. …”
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A systematic review of recurrent neural network adoption in missing data imputation by Nur Aqilah, Fadzil Akbar, Mohd Izham, Mohd Jaya, Mohd Faizal, Ab Razak, Nurul Aqilah, Zamri

“…Future development of a more robust RNN-based imputation methods that integrate optimization algorithms, such as Particle Swarm Optimization (PSO) and Stochastic Gradient Descent (SGD) will further enhance the imputation accuracy and reliability.…”
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Air quality forecasting and mapping in Malaysian urban areas: A hybrid deep learning approach by Nur'atiah Zaini

Application of genetic algorithm methods to optimize flowshop sequencing problem by Mohd Fadil, Md Sairi

“…Application of genetic algorithm method to optimize flow shop sequencing problem as the title of this project is the study about the method used in order to optimize flow shop sequencing problem. …”
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