Search Results - (( parameter adaptation based algorithm ) OR ( data distribution sensor algorithm ))
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1
Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…To enhance the selection of most highly ranking features, irrelevant features are ‘pruned’ based on determined boundary threshold. In order to estimate the quality of ‘pruned’ features, self-adaptive DE algorithm is proposed. …”
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2
Energy-Aware Clustering Routing for Mobile Ad-Hoc Sensor Networks (MASNETS)
Published 2020“…This Enhance Intra-Cluster HEED (EICHEED) proposed an adaptive routing that are suitable for MASNETs. Different experiments have been done using different parameters and numbers of results have been achieved to analyze the performance of algorithm. …”
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3
Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh
Published 2015“…The second taxonomy is a new taxonomy proposed to classify the adaptive DE algorithms in particular into two categories (DE with adaptive parameters and DE with adaptive parameters and strategies) considering the adaptive components used in this algorithm. …”
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4
Scheduled activity energy-aware distributed cluster- based routing algorithm for wireless sensor networks with non-uniform node distribution
Published 2014“…The main and definitive target of routing protocols in Wireless Sensor Networks (WSN) is passing data from the sensor nodes to the sink in most energy efficient manner besides considering the accuracy of data. …”
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5
Fuzzy Logic Based Self-Adaptive Handover Algorithm for MobileWiMAX.
Published 2013“…The proposed FuzSAHO algorithm will first self-adapt the handover parameters based on a set of multiple criteria, which includes the RSSI and MS velocity. …”
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6
A scheduled activity energy aware distributed clustering algorithm for wireless sensor networks with nonuniform node distribution
Published 2014“…However, due to the nonuniform node distribution, there is a redundancy in sensed and transmitted data in dense area. …”
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7
Novel parameter extraction for single, double, and three diodes photovoltaic models based on robust adaptive arithmetic optimization algorithm and adaptive damping method of Berndt-Hall-Hall-Hausman
Published 2022“…In this work, we present a robust adaptive Arithmetic Optimization Algorithm based on the adaptive damping Berndt-hall-hall-Hausman (RaAOAAdBHHH) approach to efficacity determine the parameters of the single, double, and three diode PV model. …”
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8
Self-adaptive Population Size Strategy Based on Flower Pollination Algorithm for T-Way Test Suite Generation
Published 2019“…Addressing this issue, this paper proposes self-adaptive population size strategy based on Flower Pollination Algorithm, called saFPA for t-way test suite generation. …”
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9
Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy
Published 2018“…The proposed design framework provides readers with the main steps required to integrate any proposed meta-algorithm into parameter and/or strategy adaptation schemes.…”
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10
Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…Recently, wireless sensor networks have employed the concept of mobile agent to reduce energy consumption and obtain effective data gathering. …”
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11
Efficient k-coverage scheduling algorithms for wireless sensor networks / Ahmed Abdullah Saleh Al-Shalabi
Published 2014“…An efficient k-coverage algorithm for sensors with fixed sensing range (Maximum Layers Scheduling algorithm - MLS) is demonstrated. …”
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12
A spawn mobile agent itinerary planning approach for energy-efficient data gathering in wireless sensor networks
Published 2017“…Moreover, each distributed MA has to carry the processing code (data aggregation code) to collect the sensory data and return back to the sink with the accumulated data. …”
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13
An Improved Distributed Scheduling Algorithm for Wireless Sensor Networks
Published 2012“…Simulation results show that the IDSA significantly outperforms a representative distributed random slot assignment algorithm (DRAND).…”
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14
On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping parameter formula
Published 2022“…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
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15
Machine learning in botda fibre sensor for distributed temperature measurement
Published 2023“…To make the sensor more reliable, temperature data must be collected over the length of the cable, or distributed data rather than point data. …”
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Analysis of LMS and NLMS noise cancellations of speech signal using Matlab Simulink / Roziahtushahila Hashim
Published 2014“…The LMS adaptive filter has several parameters which can affect their performance. …”
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17
DESIGN OF ADAPTIVE BACKSTEPPING WITH GRAVITATIONAL SEARCH ALGORITHM FOR NONLINEAR SYSTEM
Published 2014“…Gravitational search algorithm (GSA) is integrated with the designed controller in order to automatically tune its control parameters and adaptation gain since the tracking performance of the controller relies on these parameters. …”
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18
Fuzzy adaptive emperor penguin optimizer for global optimization problems
Published 2023“…To alleviate this parameter tuning problem, an adaptive mechanism can be introduced in EPO. …”
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19
Decentralized Adaptive Pi With Adaptive Interaction Algorithm Of Wastewater Treatment Plant
Published 2014“…The Pi controller parameters are obtained by using simple updating algorithm developed based on adaptive interaction theory. …”
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20
Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method.
Published 2011“…The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. …”
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