Search Results - (( wave optimization path algorithm ) OR ( pattern detection new algorithm ))
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…For static obstacle avoidance, the boundaries of the obstacle(s) are considered borders of the environment. However, the algorithm detects obstacles as a new border in dynamic obstacles once it occurs in front of the GLS waves. …”
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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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7
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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8
High impedance fault detection and identification based on pattern recognition of phase displacement computation
Published 2018“…This paper proposes a new algorithm for high-impedance-fault (HIF) detection based on phase displacement computation (PDC). …”
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Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…This tool can be used to ease the process of developing a new March test algorithm for NPSF.…”
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10
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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A new split based searching for exact pattern matching for natural texts
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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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A new hough transform on face detection and recognition using integrated histograms
Published 2015“…Hough Transform (HT) is one of the useful algorithms in pattern recognition. It is popularly used to detect straight lines, circles and curves in images. …”
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An adaptive anomaly threshold in artificial dendrite cell algorithm
Published 2017“…The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values.This causes the DCA fails to detect unlabeled data if the new pattern distinct from previous information and reduces the detection accuracy.This paper proposed an adaptive anomaly threshold for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability.In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV.From the experiments towards 12 datasets, the new version of DCA generated a better detection result than its previous version in term of sensitivity, specificity, false detection rate, and accuracy.…”
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Enhanced grey wolf optimisation algorithm for feature selection in anomaly detection
Published 2022“…Thus, this study proposes an enhanced binary grey wolf optimiser (EBGWO) algorithm for FS in anomaly detection to overcome the algorithm issues. …”
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An Improved Artificial Dendrite Cell Algorithm for Abnormal Signal Detection
Published 2018“…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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An improved artificial dendrite cell algorithm for abnormal signal detection
Published 2018“…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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Environmental pollution monitoring: a novel vectorial algorithm technique for oil detection in wastewater
Published 2023“…It is found that the new algorithm is capable of detecting the presence of oil in water samples containing many other unknown polluting elements up to 0.1 mg/L. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak
Published 2019“…The second stage is detecting jammers by integrating both lower layers by developing Integrated Combined Layer Algorithm (ICLA). …”
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Immune Multiagent System for Network Intrusion Detection using Non-linear Classification Algorithm
Published 2010“…In this work, we integrate artificial immune algorithm with non-linear classification of pattern recognition and machine learning methods to solve the problem of intrusion detection in network systems. …”
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