Search Results - (( data internalization based algorithm ) OR ( sequence optimization _ algorithm ))
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An Assembly Sequence Planning Approach with a Multi-State Particle Swarm Optimization
Published 2016“…In this paper, an approach based on a new variant of Particle Swarm Optimization Algorithm (PSO) called the multi-state of Particle Swarm Optimization (MSPSO) is used to solve the assembly sequence planning problem. …”
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Optimizing the production of valuable metabolites using a hybrid of constraint-based model and machine learning algorithms : A review
Published 2023“…This review paper summarizes research on the hybrid of constraint-based models and machine learning algorithms in optimizing valuable metabolites. The research articles published between 2020 and 2023 on machine learning and constraintbased modeling have been collected, synthesized, and analyzed. …”
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Intelligent Manufacturing Planning System Using Dispatch Rules: A Case Study in Roofing Manufacturing Industry
Published 2022“…The sequence of orders organized by the scheduling algorithm was able to minimize the changing material lead time and also maximize the number of orders to be scheduled in the production. …”
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Examining the round trip time and packet length effect on window size by using the Cuckoo search algorithm
Published 2016“…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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Neuro-Fuzzy and Particle Swarm Optimization based Model for the Steam and Cooling sections of a Cogeneration and Cooling Plant
Published 2009“…Neuro-fuzzy approach trained by a sequence of optimization algorithms-Particle Swarm Optimization (PSO) followed by Back-Propagation (BP)-is used to develop models for the steam drum pressure, steam drum water level, steam flow rate and chilled water supply temperature. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
Published 2012“…The optimal combination of λ and training sequence can be computed efficiently using a genetic permutation algorithm. …”
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Real-time anomaly detection using clustering in big data technologies / Riyaz Ahamed Ariyaluran Habeeb
Published 2019“…Based on the outcome of the analysis, this research proposed a novel framework namely real-time anomaly detection based on big data technologies (RTADBDT), along with supporting implementation algorithms. …”
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Thesis -
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Estimation of transformers health index based on condition parameter factor and hidden Markov model
Published 2018“…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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Application of genetic algorithm methods to optimize flowshop sequencing problem
Published 2008“…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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Undergraduates Project Papers -
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Assembly sequence optimization using the bees algorithm
Published 2022“…As a result, the Bees Algorithm outperforms other algorithms in dealing with the multi-modal optimization problem of assembly sequence optimization.…”
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Book Chapter -
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…To evaluate the proposed algorithm, the solutions to the TSP problem obtained from the proposed algorithm and swap sequence based PSO are compared in terms of the best solution, mean solution, and time taken to converge to the optimal solution. …”
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Data-driven neuroendocrine-pid tuning based on safe experimentation dynamics for control of TITO coupled tank system with stochastic input delay
Published 2019“…This paper addresses a data-driven neuroendocrine-PID tuning for the control of a two-input-two-output (TITO) coupled tank system with sto-chastic input time delay based on safe experimentation dynamics (SED). The SED algorithm is an optimization method used as data-driven tools to find the optimal control parameters by using the input-output (I/O) data measurement in an actual system. …”
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Detection of Workers’ Behaviour in the Manufacturing Plant using Deep Learning
Published 2023“…Utilizing machine learning algorithms, our system learns and detects intricate activities from worker behavior sequences, offering a sophisticated analysis of worker efficiency. …”
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Unequal error protection of H.264/AVC video transmitted over wireless network
Published 2015“…This work focus on the problem linked to the transmission of real time video over packet wireless network.Our objective is to define mechanism able to insuring a quality of video in spite to the problems of packet losses and transmission delays characterizing this type of network.The proposed mechanism is based Forward Error Correction (FEC) compatible with the H.264/AVC standard.This mechanism relies on a ratedistortion algorithm controlling the channel rates under a global rate constraint given by the network.This optimization takes into account the type of packet and his length; the tool of data portioning is used in our proposition.This mechanism leading to an unequal error protection of different units of coded sequence.A Reed-Solomon channel coding in application layer is adapted to unequal protected data.The experimentation results indicate the efficiency of our proposition compared to the equal error protection.…”
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A systematic review of recurrent neural network adoption in missing data imputation
Published 2025“…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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Comparative Analysis of Low Discrepancy Sequence-Based Initialization Approaches Using Population-Based Algorithms for Solving the Global Optimization Problems
Published 2021“…These algorithms can influence the convergence to find an efficient optimal solution. …”
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Assessment of integrated assembly sequence planning and line balancing optimization using metaheuristic algorithms
Published 2024“…These algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Particle Swarm Optimization (PSO). …”
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Gravitational Search Algorithm for Assembly Sequence Planning
Published 2014“…Thus, it is needed to find the optimal sequence from the feasible assembly sequences. …”
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