Search Results - (( parameter estimation machine algorithm ) OR ( parallel distribution function algorithm ))*
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Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system
Published 2023Subjects:Conference paper -
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…To implement the parallel algorithms a distributed parallel computing laboratory using easily available low cost computers is setup. …”
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Estimation of optimal machining control parameters using artificial bee colony
Published 2013“…This research employed ABC algorithm to optimize the machining control parameters that lead to a minimum surface roughness (R a) value for AWJ machining. …”
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Article -
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Comparison of machine learning algorithms for estimating mangrove age using sentinel 2A at Pulau Tuba, Kedah, Malaysia / Fareena Faris Francis Singaram
Published 2021“…The parameters involved to estimate the mangrove age are differences feature selection and different supervised machine learning algorithm. …”
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Processing time estimation in precision machining industry using AI / Lim Say Li
Published 2017“…An AI approach for processing time estimation by implementing desired input parameters and machining data is tested and completed. …”
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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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High performance visualization of human tumor growth software
Published 2008“…The platform for high performance computing of the parallel algorithms run on a distributed parallel computer system. …”
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High performance simulation for brain tumors growth using parabolic equation on heterogeneous parallel computer systems
Published 2007“…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The first step lies at the modelling of parallel applications running on heterogeneous parallel computers. …”
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Modification Of Regression Models To Solve Heterogeneity Problem Using Seaweed Drying Data
Published 2023“…After the heterogeneity parameters were excluded from the model, the support vector machine with the MM estimator showed that better significant results were obtained with 2.09% outliers. …”
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High performance simulation for brain tumours growth using parabolic equation on heterogeneous parallel computer system
Published 2007“…This paper focuses on the implementation of parallel algorithm for the simulation of brain tumours growth using one dimensional parabolic equation, design on a distributed parallel computer system. …”
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Abnormalities and fraud electric meter detection using hybrid support vector machine & genetic algorithm
Published 2023“…Genetic Algorithm (GA) is used to search for the best parameter of SVM classification by using combination of random and pre-populated genomes from Pre-Populated Database (PPD). …”
Conference Paper -
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WCDMA teletraffic performance improvement via power resource optimization using distributed parallel genetic algorithm
Published 2023“…The algorithm works by finding the minimum transmitter power with the help of Distributed Parallel Genetic Algorithm (DPGA) employed on an offload microcontroller system to form optimal beam coverage to reduce power usage of adaptive antenna at WCDMA base station. …”
Conference paper -
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Predictive modelling of machining parameters of S45C mild steel
Published 2016“…This research adopts the utilization of three types of heurestic algorithms to achieve the minimization operation; Genetic Algorithm (GA). …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS
Published 2017“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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A critical analysis of simulators in grid
Published 2015“…In parallel and distributed computing environment such as "The Grid", anticipating the behavior of the resources and tasks based on certain scheduling algorithm is a great challenging.Thus, studying and improving these types of environments becomes very difficult. …”
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Theory-guided machine learning for predicting and minimising surface settlement caused by the excavation of twin tunnels / Chia Yu Huat
Published 2024“…This is due to the data generated from the numerical model possess the pattern for the ML algorithm ease of prediction. In addition, Coati Optimization algorithm, Particle Swarm Opimisation (PSO) and Bayesian Optimsiation (BO) are integrated to identify optimal parameters and minimize settlement during twin tunnel excavation and GBT with the optimisation algorithm has shown consistent capability identifying the least SS induced by twin tunnels Keyword: …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm
Published 2012“…Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the cutting temperatures and surface roughness becomes utmost important to avoid any damage to the quality surface.This paper presents the development of new models and optimizing these models of machining parameters to minimize the cutting temperature in end milling process by integrating the genetic algorithm (GA) with the statistical approach. …”
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