Search Results - (( data (replication OR implication) means algorithm ) OR ( wave optimization path algorithm ))
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. Moreover, the proposed algorithm result are compared to some common algorithms such as the A* algorithm, Probabilistic Road Map, RRT, Bi-directional RRT, and Laser Simulator algorithm to demonstrate its effectiveness. …”
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A generalized laser simulator algorithm for mobile robot path planning with obstacle avoidance
Published 2022“…An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2021“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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Novel algorithm for mobile robot path planning in constrained environment
Published 2022“…The results demonstrated that the proposed method is able to generate efficiently an optimal collision-free path. Moreover, the performance of the proposed method was compared with the A-star and laser simulator (LS) algorithms in terms of path length, computational time and path smoothness. …”
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A dynamic replication aware load balanced scheduling for data grids in distributed environments of internet of things
Published 2018“…The simulation of the proposed algorithm shows promising results and better performance compared to the current state-of-the-art Modified Dynamic Hierarchical Replication (MDHR) algorithm. …”
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Development of a State-Space Observer for Active Noise Control Systems
Published 2009“…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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Dynamic replication aware load blanced scheduling in distributed environment / Said Bakhshad
Published 2018“…The grid processing is a viable computing surrounding. Data replication is viewed as a vital boost mechanism in data grids. …”
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Replica Creation Algorithm for Data Grids
Published 2012“…This thesis presents a new replication algorithm that improves data access performance in data grids by distributing relevant data copies around the grid. …”
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Levy slime mould algorithm for solving numerical and engineering optimization problems
Published 2022“…The proposed Levy Slime Mould Algorithm (LSMA) is a novel metaheuristic algorithm that integrates the Levy distribution into a new metaheuristic called Slime Mould Algorithm (SMA) for solving numerical and engineering problems. …”
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Efficient and scalable ant colony optimization based WSN routing protocol for IoT
Published 2020“…For this reason, many intelligent systems have been utilized to design routing algorithms to handle the network's dynamic state. In this paper, an ant colony optimization (ACO) based WSN routing algorithm for IoT has been proposed and analyzed to enhance scalability, to accommodate node mobility and to minimize initialization delay for time critical applications in the context of IoT to find the optimal path of data transmission, improvising efficient IoT communications. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…The clustering system adopted a new calculation of initial centroids has successfully determined the three regions for only a single assignment and achieving the optimal distance squared through eight given data sets. It is conflicting with the standard K-means that return different clustering structure in each run, while K-means + + replicates several times to achieve minimum objective function. …”
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Efficient relay placement algorithm using landscape aware routing (erpalar)
Published 2011“…ERP ALAR was implemented in Matlab R2009a using Genetic Algorithm (GA) with multi-objectives. GA is an optimization algorithm that simulates natural selection process as found in nature. …”
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Data-driven multi-fault detection in pipelines utilizing frequency response function and artificial neural networks
Published 2025“…The subsequent data processing stage involved the application of an ANN algorithm for pattern recognition to analyze and classify the acquired data, identifying patterns associated with the replicated fault conditions. …”
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Forecasting and Trading of the Stable Cryptocurrencies With Machine Learning and Deep Learning Algorithms for Market Conditions
Published 2023“…Thus, this proposed system employs a data science-based framework and six highly advanced data-driven Machine learning and Deep learning algorithms: Support Vector Regressor, Auto-Regressive Integrated Moving Average (ARIMA), Facebook Prophet, Unidirectional LSTM, Bidirectional LSTM, Stacked LSTM. …”
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An investigation of structural breaks on spot and futures crude palm oil returns
Published 2011“…We provide some internal and external explanations for the cause of these structural shifts in both mean and variance. Then, the study continues to investigate the implication of structural breaks in crude palm oil volatility clustering estimation process. …”
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Modified Harris Hawks Optimization Algorithm For Protein Multiple Sequence Alignment
Published 2024“…Multiple sequence alignment (msa) is a vital tool in bioinformatics for analyzing growing amounts of sequence data. However, finding similarities across large databases is an np-hard problem, meaning it is extremely difficult and time-consuming to solve exactly in real time. …”
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Robust Portfolio Mean-Variance Optimization for Capital Allocation in Stock Investment Using the Genetic Algorithm: A Systematic Literature Review
Published 2024journal::journal article
