Search Results - (( data optimization sensor algorithm ) OR ( parameter simulation based algorithm ))

Mobile data gathering algorithms for wireless sensor networks by Ghaleb, Mukhtar Mahmoud Yahya

“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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Even-odd scheduling based energy efficient routing for wireless sensor network (WSN) / Muhammad Zafar Iqbal Khan by Khan, Muhammad Zafar Iqbal

“…In future, the proposed algorithm can be further enhanced with data aggregation efficiency, probabilistically election of cluster heads, and other energy-consuming parameters.…”
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Mobile Nodes based Clustering Protocol for Lifetime Optimization in Wireless Sensor Network by Nazir, Babar, Hasbullah, Halabi

“…In this paper, we explored clustering in terms of energy efficiency for mobile WSN and proposed Mobile Nodes based Clustering Protocol for Lifetime Optimization in Wireless Sensor Network (MNCP). …”
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Using the evolutionary mating algorithm for optimizing the user comfort and energy consumption in smart building by Mohd Herwan, Sulaiman, Zuriani, Mustaffa

“…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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Mathematical modeling for SnO2 gas sensor based on second-order response by Moshayedi, Ata Jahangir, Toudeshki, Arash Mohammadi, Gharpure, Dayamanti C.

“…The data analysis has been done with Matlab software, and Genetic algorithm is further used to optimize the transfer function parameters. …”
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EZ-SEP: extended Z-SEP routing protocol with hierarchical clustering approach for wireless heterogeneous sensor network by Nurlan, Zhanserik, Zhukabayeva, Tamara, Othman, Mohamed

“…EZ-SEP was executed and compared to routing protocols such as Z-SEP, SEP, and LEACH. The proposed algorithm performed using the MATLAB R2016b simulator. …”
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Efficient and scalable ant colony optimization based WSN routing protocol for IoT by Sharmin, Afsah, Anwar, Farhat, Motakabber, S. M. A.

“…The proposed routing algorithm is simulated using MATLAB for performance evaluations. …”
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An efficient network mobility management for a 6LoWPAN mobile network in hospital environments by Shahamabadi, Mohammadreza Sahebi

“…The second scheme is a message-scheduling algorithm based on route optimization in tunnelling process between the MNNs and HA to decrease the traffic congestion at MR and packet end-toend delay. …”
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Optimization Method Using Modified Harmony Search For Coverage And Energy Efficiency In Wireless Sensor Network by Halim, Nurul Hamimi

“…Coverage and energy efficiency metrics are two fundamental issues for almost all types of application in wireless sensor network (WSNs).Coverage reflects how well an area is monitored by sensor nodes and in energy efficient networks where less energy is consumed to provide the same level of services.These twin specifics are presented to evaluate the performance of a wireless sensor network.Due to its simplicity and ease of analysis,full coverage is widely implemented in many theoretical studies.However,sometimes full coverage is not the best way to represent some real-world application due to its strong restrictions and its deterministic characteristics.In this thesis,Modified Harmony Search algorithm (MHS) is proposed to achieve a sensor node deployment such that the covered area is optimal and data transfer has low energy consumption.Through computer simulations, experimental results verified that the proposed method improved the coverage of area in compare to some related methods.Based on the result obtain from every experiments,coverage area percentage performance is affected by the number of hotspots.This is shown by Harmony Search (HS) based method where the coverage area percentage increases as the number of hotspot increase. …”
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FuMAM: fuzzy-based mobile agent migration approach for data gathering in wireless sensor networks by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

“…Instead of transporting data from the nodes to the processing unit (e.g., sink) for data gathering, the MA visits each node, and thus, it performs data gathering locally. …”
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Single fitness function analysis of energy-consumption and radio bandwidth management in coverage area problems by Kalid Abdlkader Marsal

Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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QoS BASED ENERGY EFFICIENT ROUTING IN WIRELESS SENSOR NETWORK by NAZIR, BABAR

“…Clustering within normal sensor nodes is done by optimizing the network/coverage lifetime through a cluster-head-selection algorithm and a sleep/wake scheduling algorithm. …”
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Green anaconda optimization based energy aware clustering protocol for 6G wireless communication systems by Motwakel, Abdelwahed, Hassan Abdalla Hashim, Aisha, Mengash, Hanan Abdullah, Alruwais, Nuha, Yafoz, Ayman, Alsini, Raed, Edris, Alaa

“…Therefore, this study presents a new Green Anaconda Optimization Based Energy Aware Clustering Protocol (GAOB-EACP) approach for WSN. …”
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Self-Organized Wireless Sensor Network (SOWSN) for dense jungle applications by Hakim, Galang Persada Nurani, Habaebi, Mohamed Hadi, Islam, Md Rafiqul, Alghaihab, Abdullah, Yusoff, Siti Hajar, Adesta, Erry Yulian Triblas

“…The third feature is the introduction of the (Levenberg Marquardt artificial neural network (LM-ANN) for Adaptive Dynamic Power Control to further optimize the transmitter power levels, radio modulation, Spreading Factor configurations, and settings of the employed SOWSN LoRaWAN nodes based on predicted wireless transmission link quality parameters. …”
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DC-based PV-powered home energy system by Sabry, Ahmad H.

“…A controller based on an algorithm of one time maximum power point (MPP) is proposed to mitigate those losses. …”
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Metaheuristic multi-hop clustering optimization for energy-efficient wireless sensor network by Vincent Chung, Norah Tuah, Kit Guan Lim, Min Keng Tan, Ismail Saad, Kenneth Tze Kin Teo

“…On the other hand, multi-hop optimization algorithm will form a multi-hop network by transmitting data to base station (BS) through data multi-hopping between sensor nodes. …”
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Multi-mobile agent itinerary planning algorithms for data gathering in wireless sensor networks: a review paper by Qadori, Huthiafa Q., Ahmad Zukarnain, Zuriati, Mohd Hanapi, Zurina, Subramaniam, Shamala

“…Despite the advantages of multi-agent itinerary planning, finding the optimal number of distributed mobile agents, source nodes grouping, and optimal itinerary of each mobile agent for simultaneous data gathering are still regarded as critical issues in wireless sensor network. …”
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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…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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Human health status IoT device using data optimization algorithm / Albin Lemuel Kushan ... [et al.] by Kushan, Albin Lemuel, Anuar, Muhammad Hazwan, Mohd Supir, Mohd Hafifi, Ahmad Fadzil, Ahmad Firdaus, Zolkeplay, Anwar Farhan

“…This project aims to produce a device that can be used to identify the current health status of a person using sensor and a data optimization algorithm. Furthermore, this project uses CT-UNO (Arduino Uno) microcontroller as its base together with the LM-35 Body Temperature sensor and the Pulse Sensor for reading heart rate, and a web system to manage the data collected. …”
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