Search Results - (( using function max algorithm ) OR ( basic localization based algorithm ))
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1
Maximum 2-satisfiability in radial basis function neural network
Published 2020“…This paper presents a new paradigm in using MAX2SAT by implementing in Radial Basis Function Neural Network (RBFNN). …”
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Fair uplink bandwidth allocation and latency guarantee for mobile WiMAX using fuzzy adaptive deficit round robin
Published 2014“…In this paper, an efficient bandwidth allocation algorithm for the uplink traffic in mobile WiMAX is proposed. …”
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3
Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…We introduced two new approaches to normalization techniques to enhance the K-Means algorithms. This is to remedy the problem of using the existing Min-Max (MM) and Decimal Scaling (DS) techniques, which have overflow weakness. …”
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Thesis -
4
Effective downlink resource management for wimax networks
Published 2018“…Our EDRM framework involves three functions: Class-Based Scheduling (CBS) algorithm, Dynamic Bandwidth Allocation (DBA) scheme and Link Session Management (LSM) policy. …”
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5
Modern fuzzy min max neural networks for pattern classification
Published 2019“…To build an efficient classifier model, researchers have introduced hybrid models that combine both fuzzy logic and artificial neural networks. Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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6
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
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A hybrid range-free algorithm using dynamic communication range for wireless sensor networks
Published 2020“…Distance-Vector Hop (DV-Hop) is a representative range-free localization algorithm, which is widely utilized to locate node position in location-based application. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Adaptive RS-group scheduling for WiMAX multihop relay
Published 2010“…This paper proposes mesh topology for IEEE 802.16j using adaptive RS group scheduling. The proposed scheduling algorithm introduces new signalling to support functions such as soft and hard horizontal-RS neighbour scanning, bandwidth request, forwarding of PDUs and connection management. …”
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Proceeding Paper -
10
Designing and Developing an Intelligent Congkak
Published 2011“…Therefore the project want to try to rectify this issue by trying to develop an Intelligent Congkak System that also implemented NN and try answer research question such as this: “What is the best Congkak evaluation function for training NN for game playing?” and “Can Min-Max algorithm (MM) be speeded up by using NN as a forward-pruning method?”. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…Nevertheless, as the representative range-free localization scheme, Distance Vector-Hop (DV-Hop) localization algorithm demonstrates extremely poor localization accuracy under anisotropic wireless sensor networks. …”
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13
Performance comparison of differential evolution and particle swarm optimization in constrained optimization
Published 2012“…Particle swarm optimization (PSO) and differential evolution (DE) are among the well-known modern optimization algorithms. This paper presents a comparative study for min-max constrained optimization using PSO and DE. …”
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14
Local search manoeuvres recruitment in the bees algorithm
Published 2011“…Swarm intelligence of honey bees had motivated many bioinspired based optimisation techniques. The Bees Algorithm (BA) was created specifically by mimicking the foraging behavior of foraging bees in searching for food sources.During the searching, the original BA ignores the possibilities of the recruits being lost during the flying.The BA algorithm can become closer to the nature foraging behavior of bees by taking account of this phenomenon.This paper proposes an enhanced BA which adds a neighbourhood search parameter which we called as the Local Search Manoeuvres (LSM) recruitment factor.The parameter controls the possibilities of a bee extends its neighbourhood searching area in certain direction.The aim of LSM recruitment is to decrease the number of searching iteration in solving optimization problems that have high dimensions.The experiment results on several benchmark functions show that the BA with LSM performs better compared to the one with basic recruitment.…”
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Conference or Workshop Item -
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Design And Implementation Of Low Passband Ripple Digital Down Converter Filter For Software Defined Radio Transceiver
Published 2011“…The proposed DDC filters incorporate of Remez algorithm and Mini-max algorithm to reduce the error rate in the filter response. …”
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16
Improved handover decision algorithm using multiple criteria
Published 2018“…Conventionally, a device that is mobile can be used to attain vertical handover functional by weighing in only an aspect, which refers to Received Signal Strength (RSS). …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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A quantum-inspired particle swarm optimization approach for environmental/economic power dispatch problem using cubic criterion function
Published 2018“…Many-objective EED problems are defined by using a cubic criterion function, and a max/max price penalty factor is considered to convert all the objectives into a single objective to compare the final results with other well-known methods found in the literature like Lagrangian relaxation, particle swarm optimization, simulated annealing, and quantum-behaved bat algorithm. …”
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Vision Based Calibration and Localization Technique for Video Sensor Networks
Published 2009“…Very few of these localization algorithms use vision based technique. …”
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Cyclic Path Planning Of Hyper-Redundant Manipulator Using Whale Optimization Algorithm
Published 2023Article
