Search Results - (( data classification means algorithm ) OR ( evolution optimization sensor algorithm ))
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1
Cluster head selection optimization in wireless sensor network via genetic-based evolutionary algorithm
Published 2020“…Genetic-based evolutionary algorithms such as Genetic Algorithm (GA) and Differential Evolution (DE) have been popularly used to optimize cluster head selection in WSN to improve energy efficiency for the extension of network lifetime. …”
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2
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…In a previous research, a relocating algorithm for mobile sensor network had been introduced and the goal was to save energy and prolong the lifetime of the sensor networks using Particle Swarm Optimization (PSO) where both of sensing radius and travelled distance had been optimized in order to save energy in long-term and shortterm. …”
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3
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Clustering is one of the means in data mining of predicting the class based on separating the data categories from similar features. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…Methods for improving supervised and unsupervised classification of remotely sensed data were developed in this study. …”
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5
Design, optimization and fabrication of a climbing six articulated-wheeled robot using artificial evolution and 3D printing
Published 2015“…In this research, an artificial evolution approach utilizing Single-Objective Evolutionary Algorithm (SOEA) and Multi-Objective Evolutionary Algorithm (MOEA) respectively are investigated in the automatic design and optimization of the morphology of a Six Articulated-Wheeled Robot (SAWR) with climbing ability. …”
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6
An improved gbln-pso algorithm for indoor localization problem in wireless sensor network
Published 2022“…Then, we compared the result with Particle Swarm Optimization (PSO), Differential Evolution Particle Swarm Optimization (DEPSO), Health Particle Swarm Optimization (HPSO) and Global best Local Neigborhood Particle Swarm Optimization (GbLN-PSO) algorithm. …”
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7
Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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An improved data classification framework based on fractional particle swarm optimization
Published 2019“…Furthermore, the proposed MOFPSO algorithm is hybridized with Back-Propagation (BP), Elman Recurrent Neural Networks (RNN) and Levenberg-Marquardt (LM) Artificial Neural Networks (ANNs) to propose an enhanced data classification framework, especially for data classification applications. …”
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9
Effective k-Means Clustering in Greedy Prepruned Tree-based Classification for Obstructive Sleep Apnea
Published 2022“…GPrTC algorithm showed better classification accuracies than k-means clustering in almost all the assigned datasets. …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building
Published 2023“…EMA belongs to the evolutionary computation group of nature-inspired metaheuristic algorithms and offers a promising solution. A comparative analysis is conducted with other well-known algorithms such as Particle Swarm Optimization (PSO), Differential Evolution (DE), Ant Colony Optimization (ACO), Biogeography-Based Optimization (BBO), Teaching-Learning Based Optimization (TLBO), and Beluga Whale Optimization (BWO). …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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12
Dealing with Routing Hole Problem in Multi-hop Hierarchical Routing Protocol in Wireless Sensor Network
Published 2019“…In the proposed work, the focused problem is how to reduce the communication energy consumption and to avoid the routing hole problem by optimized routing algorithms. First, a routing hole detection algorithm is proposed prior to designing the routing protocol which decreases about 30 percent energy consumption rate, detection time and detection overhead. …”
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13
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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14
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Phase 1 is mainly to evaluate the performance of clustering algorithm (K-Means and FCM). Phase 2 is to study the performance of proposed integration system which using the data clustered to be used as train data for Naïve Bayes classifier. …”
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15
Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…The main objective in this study is to determine the better method to be used to find the centres in the Radial Basis Functional Link Nets for data classification. Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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A secure trust aware ACO-Based WSN routing protocol for IoT
Published 2022“…The performance of the proposed routing algorithm is demonstrated through MATLAB. Based on the proposed system, to find the secure and optimal path while aiming at providing trust in IoT environment, the average energy consumption is minimized by nearly 50% even as the number of nodes has increased, as compared with the conventional ACO algorithm, a current ant-based routing algorithm for IoT-communication, and a present routing protocol RPL for IoT.…”
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Logistic regression methods for classification of imbalanced data sets
Published 2012“…Classification of imbalanced data sets is one of the important researches in Data Mining community, since the data sets in many real-world problems mostly are imbalanced class distribution. …”
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18
Artificial neural controller synthesis for TORCS
Published 2015“…The results showed: (1) DE hybrid FFNN could generate optimal controllers, (2) the proposed fitness function had successfully generated the required car's racing controllers, (3) the proposed minimization algorithm had been successfully minimize the number of RF sensors used, (4) the PDE algorithm could be implemented to generate optimal solutions for car racing controllers, and (5) the combination of components for average car speed and distance between the car and track axis is very important compared to other components. …”
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19
Use of hybrid classification algorithm for land use and land cover analysis in data scarce environment
Published 2013“…In conclusion, hybrid classification as a combination of k-means and support vector machine algorithms and post-classification comparison change detection technique can be used to monitor land cover changes in Halabja city, Iraq. …”
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20
Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper
