Search Results - (( automatic classification mining algorithm ) OR ( using optimization sensor algorithm ))
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1
Data mining of protein sequences with amino acid position-based feature encoding technique
Published 2014“…Biological data mining has been emerging as a new area of research by incorporating artificial intelligence and biology techniques for automatic analysis of biological sequence data. …”
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2
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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3
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…A well known task is classification that predicts the class of new instances using known features or attributes automatically. …”
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4
Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…Two classification approaches which are the descriptive statistical and data mining are used in order to examine the classification of the gender by using the five extracted features. …”
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5
A novel ensemble decision tree-based CHi-squared Automatic Interaction Detection (CHAID) and multivariate logistic regression models in landslide susceptibility mapping
Published 2014“…An ensemble algorithm of data mining decision tree (DT)-based CHi-squared Automatic Interaction Detection (CHAID) is widely used for prediction analysis in variety of applications. …”
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6
Study Of Modified Training Algorithm For Optimized Convergence Speed Of Neural Network
Published 2016“…First proposed algorithm is the combination of momentum algorithm with adaptive learning rate (ALR) algorithm, and second proposed algorithm is the combination of momentum algorithm with automatic learning rate selection (ALRS) algorithm. …”
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7
A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…Particle Swarm Optimization has been used in the proposed algorithm to minimize the fitness function. …”
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Simulated Kalman Filter optimization algorithm for maximization of wireless sensor networks coverage
Published 2019“…It had been successfully used for optimization of many engineering problems. …”
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Node placement optimization using extended virtual force and cuckoo search algorithm in wireless sensor network
Published 2014“…This study proposed Extended Virtual Force and Cuckoo Search (EVFCS) algorithm with a combination of EVFA and CS algorithm to find an optimal node placement. …”
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10
Integration of object-based image analysis and data mining techniques for detailes urban mapping using remote sensing
Published 2015“…This algorithm represents the decision tree knowledge model, enables fast classification of intra-urban classes, and disables subjectivities related to the interaction with analysts. …”
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11
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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Global optimization method for continuous - Time sensor scheduling
Published 2010“…We consider a situation in which several sensors are used to collect data for signal processing since operating multiple sensors simultaneously canses system interference, only one sensor can be active at any one time.The problem of scheduling a discrete-valued optimal control problem.This problem cannot be solved using conventional optimization problem.The Transformed problem is then decomposed into a bi-level optimization problem, which is solved using a discreate filled function method in conjunction with a conventional optimal control algorithm.Numerical results show that our algorithm is robust, efficient, and reliable in attaining a near globally optimal solution.…”
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Provisioning an energy efficient with maximum coverage WSN through biological inspired sensor node placement
Published 2023Conference Paper -
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors
Published 2025“…One of the powerful optimization algorithms that is used for feature selection is the Whale Optimization Algorithm (WOA), which is a nature-inspired metaheuristic optimization algorithm that mimics the social behavior of humpback whales. …”
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15
Optimizing Visual Surveillance Sensor Coverage Using Dynamic Programming
Published 2017“…The main contribution of the paper is to introduce a dynamic programming algorithm, which defines an optimal policy for solving the visual sensor coverage problem. …”
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A Novel Polytope Algorithm based on Nelder-mead method for localization in wireless sensor network
Published 2024“…Results: Simulation results perfectly showed that the suggested localization algorithm based on NMM can carry out a better performance than that of other localization algorithms utilizing other op- timization approaches, including a particle swarm optimization, ant colony (ACO) and bat algorithm (BA). …”
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Multi-objective biological mimicry optimization algorithm for WSN sensor node placement
Published 2023Conference Paper -
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A Green Clustering Protocol for Mobile Sensor Network Using Particle Swarm Optimization
Published 2016“…One of the methods that can improve the utilization of sensor nodes batteries is the clustering method. In this paper, we propose a green clustering protocol for mobile sensor networks using particle swarm optimization (PSO) algorithm.…”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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20
Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper
Published 2017“…The review shows that most of the algorithms used one parameter to find the optimal number of mobile agents in multi-agent itinerary planning without utilizing other parameters. …”
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