Search Results - (( write classification swarm algorithm ) OR ( basic optimization sensor algorithm ))
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1
Feature selection based on particle swarm optimization algorithm for sentiment analysis classification
Published 2021“…Furthermore, the proposed algorithm solves the complex background problems about noise data and feature selection that affect the classification performance on sentiment analysis. …”
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2
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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3
A New Swarm-Based Framework for Handwritten Authorship Identification in Forensic Document Analysis
Published 2014“…In this chapter, feature selection is explored in order to find the most unique individual significant features which are the unique features of individual’s writing. This chapter focuses on the integration of Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS) feature selection technique into the proposed hybrid of Writer Identification framework 386 S.F. …”
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A new swarm-based framework for handwritten authorship identification in forensic document analysis
Published 2014“…In this chapter, feature selection is explored in order to find the most unique individual significant features which are the unique features of individual’s writing. This chapter focuses on the integration of Swarm Optimized and Computationally Inexpensive Floating Selection (SOCIFS) feature selection technique into the proposed hybrid of Writer Identification framework and feature selection framework, namely Cheap Computational Cost Class Specific Swarm Sequential Selection (C4S4). …”
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5
On Clustering Algorithm Of Coverage Area Problems In Wireless Sensor Networks
Published 2024“…For the proliferation of wireless sensor network, in different environments, an escalation in the lifetime of wireless sensors is mandatory, because among the basic issues concerning WSN is a successful effort to document the coverage of the number of target fields, while maximizing the lifetime of this network. …”
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Development an accurate and stable range-free localization scheme for anisotropic wireless sensor networks
Published 2022“…This study developed an optimized variation of the DV-Hop localization algorithm for anisotropic wireless sensor networks. …”
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7
Efficient transmission based on genetic evolutionary algorithm
Published 2022“…In this paper, an energy-saving mechanism based on genetic algorithm in wireless sensor network (WSN) is proposed. …”
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Proceedings -
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan
Published 2022“…Wireless Sensor Network (WSN) is basically composed of battery powered devices which have an obvious limitation of energy on sensors nodes, so it is the foremost motivation to develop a method to save energy of wireless sensor networks where networks are kept alive for a long time. …”
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9
A Survey Of Supervised Machine Learning In Wireless Sensor Network: A Power Management Perspective
Published 2013“…This survey paper is focused on the discussion of best optimal path routing algorithms in wireless sensor networks by using supervised machine learning approaches. …”
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10
Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…The performances obtained show that the optimized APFLC is better than the non-optimize APFLC in terms of RMSE and the settling time.…”
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11
A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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A hybrid prediction model for pipeline corrosion using Artificial Neural Network with Particle Swarm Optimization
Published 2018“…This project aims to develop a hybrid prediction Model which can target specific corrosion damage mechanisms. The basic ANN Model will be improved by integrating the Particle Swarm Optimization (PSO) algorithm to achieve a better and optimal performance. …”
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A review of navigation systems (integration and algorithms)
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Performance study of the coexistence of Wireless Sensor Networks (WSN) and Wireless Local Area Networks (WLAN) / Muhammad Adib Haron … [et al.]
Published 2008“…To implement WSN integrated with cognitive radio techno 10gy, a new algorithm that provides access mechanism is needed to interactively working with sensor nodes hardware. …”
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Research Reports -
15
Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems
Published 2009“…We then consider the task of determining near globally optimal solutions of discrete-valued optimal control problems. …”
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16
Development of control algorithm for a new 12s-6p single phase field excited flux switching motor
Published 2020“…For position detection, algorithms merely need a basic infrared transceiver sensor. …”
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Design and development of detection scheme using multiline image scanning for aerial mapping of a simulated rice paddy field and implemented on unmanned aerial vehicle / Mohamad Fa...
Published 2018“…A conventional analog camera as front end sensor was used in this work as it could provide vast raw image data that can be utilized to identify the captured image using the designed algorithm. …”
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18
Design and development of detection scheme using multiline image scanning for aerial mapping of a simulated rice paddy field and implemented on unmanned aerial vehicle / Mohamad Fa...
Published 2018“…A conventional analog camera as front end sensor was used in this work as it could provide vast raw image data that can be utilized to identify the captured image using the designed algorithm. …”
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