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Dynamic Sensor Scheduling for Data Size Reduction in a Sensor Cloud System Based on Minimum Reconstruction Error

WIRELESS PERSONAL COMMUNICATIONS 2024年第3期135卷 1423-1447页

作者： Shylashree, N. Kumar, Sachin VTU RV Coll Engn Dept Elect & Commun Bengaluru 560059 India South Ural State Univ Big Data & Machine Learning Lab Chelyabinsk Russia

Sensing and subsequent analysis of the environmental data of a given geographical area is an essential requisite for the planned development of that region. Nowadays, IoT Sensor-Cloud ecosystem has been adopted to collect data from IoT sensors and transmit it to the chosen Cloud Server for further processing and dissemination. In a large Wireless Sensor Network formed by the IoT sensors, there will be a significant amount of redundancy in the dataset when the nodes are placed closely, and the sensed data varies slowly and gradually with regard to time and space. Then, avoiding redundant data transmission can lead to lower energy consumption and communication overhead. Adaptive subset selection of sensor nodes for data size reduction in a Wireless Sensor Network is an approach to efficiently managing the amount of data transmitted within the network. Then, in the current time schedule, it is possible to optimally select a subset of the sensor nodes for data collection without very much affecting the overall data fidelity. An optimal sensor node subset selection scheme that reduces the communication load with minimum information loss is proposed to achieve this task. The unselected nodes are put in sleep mode, which consequently results in lower sensor energy expenditure. The subset selection algorithm is implemented based on the derivative-free pattern search optimizer that minimizes the reconstruction error during the associated extrapolation. This approach differs entirely from the Compressive Data Gathering approach. The simulation results reveal that the performance of the proposed scheme is superior to other similar competitive methods in terms of the mean square error, which is found to be 1.95, with the percentage participation nodes equal to 50% and when the sensor data is uniformly distributed over 20 and 30 units.

关键词： pattern search algorithm Grid data extrapolation Minimum reconstruction error Keyframes Intermediate frames Wakeup duty cycle

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Genetic algorithm-Driven Cover Set Scheduling for Longevity in Wireless Sensor Networks

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2025年第3期16卷 1104-1112页

作者： Larhlimi, Ibtissam Lmkaiti, Mansour Lachgar, Maryem Ouchitachen, Hicham Darif, Anouar Limati, Hicham Mouncif Sultan Moulay Slimane Univ LAB Polydisciplinary Fac Khouribga Morocco

This paper aims to develop an efficient scheduling approach based on Genetic algorithms to optimize energy consumption and maximize the operational lifetime of Wireless cial for prolonging the operational lifespan of wireless sensor networks (WSNs) that include a substantial number of sensors. Simultaneously activating all sensors results in a fast depletion of energy, thus diminishing the overall lifespan of the network. To address this issue, it is necessary to schedule sensor activity in an effective manner. This task, known as the maximum coverage set scheduling (MCSS) problem, is highly complex and has been demonstrated to be NP-hard. This article presents a customized genetic algorithm designed to tackle the MCSS problem, aiming to improve the longevity of Wireless Sensor Networks (WSNs). Our methodology effectively detects and enhances combinations of coverage sets and their corresponding schedules. The program incorporates key criteria such as the detection ranges of individual sensors, their energy levels, and activity durations to optimize the overall energy efficiency and operational sustainability of the network. The performance of the suggested algorithm is assessed through simulations and compared to that of the Greedy algorithm and the pattern search algorithm. The results indicate that our genetic algorithm not only maximizes network lifetime but also enhances the efficiency and efficacy of solving the MCSS problem. This represents a significant improvement in managing the energy consumption in WSNs.

关键词： Maximum network lifetime wireless sensor network coverage sets scheduling genetic algorithm pattern search algorithm

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Smart carrot chasing guidance law for path following of unmanned surface vehicles

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT 2024年第3期238卷 567-576页

作者： Unal, Osman Akkas, Nuri Atali, Gokhan Ozkan, Sinan Serdar Sakarya Univ Appl Sci Dept Mech Engn Sakarya Turkiye Sakarya Univ Appl Sci Dept Mechatron Engn Sakarya Turkiye Sakarya Univ Appl Sci Dept Mech Engn TR-54050 Serdivan Sakarya Turkiye

Carrot chasing guidance law is one of the most widely used path following algorithms due to its simplicity and ease of implementation;however, it has a fixed parameter which leads to large cross-tracking errors during different navigational conditions. This study proposes an innovative approach to carrot chasing algorithm to minimize cross-tracking errors. pattern search optimization technique is integrated with carrot chasing guidance law to determine unique virtual target points obtained by flexible parameters instead of a fixed parameter. Proposed smart carrot chasing guidance law (SCCGL) provides stable and accurate path following even for different navigational conditions of unmanned surface vehicle (USV). To the best of our knowledge, we are the first to apply pattern search optimization technique to carrot chasing guidance law while USV is performing multi-tasks of predefined paths. This novelty significantly reduces both cross tracking errors and computational costs. Firstly, SCCGL is tested and compared with traditional carrot chasing algorithm in the numerical simulator for several navigational conditions such as different lists of waypoints, different initial locations, and different maximum turning rates of USV. SCCGL automatically determines optimal parameters to make stable and accurate navigation. SCCGL significantly reduces cross tracking errors compared to classical carrot chasing algorithm. This is the first contribution of this paper. Secondly, genetic algorithm optimization method has been implemented to carrot chasing guidance law instead of pattern search optimization technique. Genetic algorithm causes the total simulation time to be quite long. The proposed SCCGL (pattern search integrated carrot chasing guidance law) gives optimum results 20 times faster than the genetic algorithm. This is the second and main contribution of developed SCCGL method. It is observed that SCCGL provides best navigation with minimum cross-tracking errors and mini

关键词： Path following algorithm carrot-chasing guidance law pattern search algorithm cross-tracking error unmanned surface vehicle

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Improved Cooperation search Optimization algorithm for Infinite Impulse Response System Identification

ELECTRICA

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ELECTRICA 2024年第3期24卷 733-+页

作者： Ersali, Cihan Hekimoglu, Baran Batman Univ Dept Elect & Elect Engn Batman Turkiye

This study addresses the challenges of infinite impulse response (IIR) system identification by introducing an improved cooperation search algorithm (ICSA). Improved cooperation search algorithm enhances the original cooperation search algorithm (CSA) through the integration of a pattern search algorithm and opposition-based learning, aiming to improve both exploration and exploitation capabilities. The algorithm's performance was evaluated against diverse IIR plants of varying orders using convergence analysis, scatter plots, and statistical metrics. Results demonstrate ICSA's superiority over CSA, achieving significantly lower mean squared error (MSE) values across different system orders and model types. Notably, ICSA outperformed CSA by up to 27 orders of magnitude for matched-order models and up to 95.85% for reduced-order models. The algorithm also exhibited more consistent performance, with substantially lower standard deviations in many cases. Statistical validation through the Wilcoxon signed-rank test further confirmed ICSA's enhanced performance. This research highlights ICSA's efficacy in producing efficient IIR systems, demonstrating its potential for more accurate system identification compared to existing methods.

关键词： Cooperation search algorithm (CSA) infinite impulse response (IIR) opposition-based learning (OBL) pattern search algorithm system identification

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Structural damage detection based on incomplete modal data using pattern search algorithm

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JOURNAL OF VIBRATION AND CONTROL 2013年第6期19卷 821-833页

作者： Kourehli, S. S. Amiri, G. Ghodrati Ghafory-Ashtiany, M. Bagheri, A. Islamic Azad Univ Dept Civil Engn Sci & Res Branch Tehran Iran Iran Univ Sci & Technol Sch Civil Engn Ctr Excellence Fundamental Studies Struct Engn Tehran Iran Int Inst Earthquake Engn & Seismol Struct Dept Tehran Iran Univ Pittsburgh Dept Civil & Environm Engn Pittsburgh PA USA

Incomplete sensed data in structures have made exact structural damage detection a serious challenge. In this paper, an effective method is presented for damage detection and estimation in structures based on incomplete modal data of a damaged structure via a pattern search algorithm. An objective function based on the condensed mass and stiffness matrices is formulated. The proposed method determines the damage to structural elements using optimization of the objective function by using pattern search algorithm. The performance of the presented method has been verified through two numerical examples, namely, a two-span continuous beam and a three-story plane frame with and without noise in the modal data containing several damages. Also, the effect of the discrepancy in mass and stiffness between the finite-element model and the actual tested dynamic system has been investigated. Furthermore, the experimental data from the vibration test of a mass-stiffness system are used for verification of the proposed approach. The results show that the presented method is sensitive to the location and severity of structural damage in spite of the incomplete modal data.

关键词： Damage detection incomplete modal data optimization pattern search algorithm

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Coordinated optimal control of active power of wind farms considering wake effect

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ENERGY REPORTS 2022年 8卷 84-90页

作者： Shen, Yu Xiao, Tannan Lv, Qifeng Zhang, Xuemin Zhang, Yangfan Wang, Yimei Wu, Jinfang State Grid Xin Yuan Co Zhangjiakou Wind & Solar Power Energy Demonstrat Jianshe West St 15 Zhangjiakou 075000 Peoples R China Tsinghua Univ Shuangqin Rd 30 Beijing 100084 Peoples R China State Grid Jibei Elect Power Co Ltd Elect Power Res Inst Caishikou South St 56 Beijing 100054 Peoples R China

In a large-scale wind farm, under the influence of the wake effect, the single-machine maximum power extraction control strategy would not be able to function at the ideal optimal value. It is important to study the coordinated operation strategy of the wind farm under the wake effect to improve the output power of wind farms and improve the economic benefit. In this paper, a practical wake model called the PARK model is used and a wake superposition model based on energy balance is derived. Based on these models, an optimization problem is formulated to maximize the output power of the wind farm considering the wake effect. Taking the Horns Rev offshore wind farm as an example, the stochastic points method, particle swarm optimization, and the pattern search algorithm are implemented and compared with the single-machine maximum power extraction algorithm. Test results show that the particle swarm optimization and the pattern search algorithm have better performance. The output power of the wind farm increases by about 10 percent. The particle swarm optimization requires less computation while the pattern search algorithm obtains better and more practical results. Finally, the pattern search algorithm is used to improve economic benefits under different wind conditions. (C) 2021 The Authors. Published by Elsevier Ltd.

关键词： Wake effect Coordinated operation strategy Particle swarm optimization pattern search algorithm

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Thermodynamic analysis of general heat engine cycle with finite heat capacity rates for power maximization

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CASE STUDIES IN THERMAL ENGINEERING 2022年 35卷

作者： Kim, Soyeon Baik, Young-Jin Kim, Minsung Chung Ang Univ Dept Intelligent Energy & Ind 84 Heukseok Ro Seoul 06974 South Korea Korea Inst Energy Res Thermal Energy Convers Syst Lab 152 Gajeong Ro Dajeon 34129 South Korea Chung Ang Univ Sch Energy Syst Engn 84 Heukseok Ro Seoul 06974 South Korea

In this study, the ideal cycles with finite heat capacity rates is investigated theoretically to maximize power generation using a sequential Carnot cycle model. Although the Carnot efficiency is important, it is limited to evaluating only in terms of heat source/sink temperatures. For the actual heat engine, maximization of power generation is more important than cycle thermal efficiency when utilizing low-grade heat sources such as a waste heat. In this study, power generation optimization is numerically simulated under the fixed conditions of heat source temperatures, heat source flow rate and heat sink temperature. Effect by two design variables, compressor exit temperature and evaporator size ratio, were evaluated during cycle optimization. The optimization was performed using the pattern search algorithm (PSA) under a given thermal capacitance rate ratios and size of heat exchanger (UA) conditions. As a result, designing compressor exit temperature for maximizing the heat received from heat sources does not always maximize the power, but the higher the UA makes the optimum temperature lower, and the power output higher. These idealistic approaches can be useful in designing of cycle where the power maximization is crucial.

关键词： Power maximization Sequential carnot cycle Waste heat recovery pattern search algorithm Trilateral cycle

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Flame detection by heat from the infrared spectrum: Optimization and sensitivity analysis

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FIRE SAFETY JOURNAL 2022年第0期133卷 1页

作者： Bordbar, Hadi Alinejad, Farid Conley, Kevin Ala Nissila, Tapio Hostikka, Simo Aalto Univ Sch Engn Espoo Finland Aalto Univ Sch Chem Engn Dept Chem & Mat Sci Espoo Finland Aalto Univ QTF Ctr Excellence Dept Appl Phys POB 11000 FI-00076 Espoo Finland Loughborough Univ Interdisciplinary Ctr Math Modeling Loughborough LE11 3TU Leics England Loughborough Univ Dept Math Sci Loughborough LE11 3TU Leics England

Accurate detection of unwanted fires at their early stage is crucial for efficient mitigation and loss prevention. Moreover, the detection strategy must avoid false alarms and the associated disruptions in workplaces. Thermal radiation-based flame detection is the fastest detection method and is commonly used in critical industrial spaces, such as air hangars and petroleum manufacturing and storage. The main challenge is distinguishing the radiation of flames from other sources, e.g., hot objects or the Sun. The principles of radiation-based flame detection have been known for a long time, but open data and worked-out feasibility studies are rare. This work takes advantage of the recent advances in experimental and numerical methods of characterizing the infrared spectra. Combining high-resolution spectra from flames and blackbody emitters with virtual low-pass filters allows us to simulate the response of a hypothetical sensor. To maximize the difference between flame and blackbody responses, we use a pattern search algorithm to find optimal filtering wavelengths for two different detection strategies based on three or four optical low-pass filters. The optimal wavelengths are reported along with the sensitivity of the detection signal to the filter non-ideality. Our results give guidelines for design of efficient and highly selective flame-radiation-based fire detection sensors.

关键词： Flame detection Spectral radiation Optical filter Flame emission spectra Optimization pattern search algorithm

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Improved pattern search algorithm Based on Optimal Design of Fixture Locator Layout

Improved Pattern Search Algorithm Based on Optimal Design of...

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10th IEEE International Conference on Mechatronics and Automation (ICMA)

作者： Guo, Hua Wang, Kedian Liu, Zhihui Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shaanxi Peoples R China Xi An Jiao Tong Univ Sch Mech Engn State Key Lab Mfg Syst Engn Xian 710049 Shaanxi Peoples R China

ISBN: (纸本)9781467355605

In the machining and detecting process, fixture is always one important part. Because it offers apropriate locating and clamping for the process, and a fixture with its locating accuracy affects much on the final accuracy. Therefore it is necessary to analysis the performance of a fixture, and the optimal design of fixture layout is a common way to improve its performance. Around the optimization design of fixture locator layout, firstly, the model of locators' tiny displacement and location variation of a workpiece was built and linearized to achieve a measurement of the fixture locating accuracy;secondly, to improve the optimal result of optimization algorithm, pattern search algorithm was introduced into locator layout design and improved;finally, one blade model was taken into an example, corresponding fixture layout optimization design was achieved. It is proved by the example that the optimization design method proposed can get a better computing result and a much less iterate steps.

关键词： Locating accuracy fixture design locator layout design pattern search algorithm

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Dynamic Optimal Operation of Microgrid for Reduced Costs Based on pattern search algorithm

Dynamic Optimal Operation of Microgrid for Reduced Costs Bas...

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International Conference on Electrical Machines and Systems (ICEMS)

作者： Xiao, Hao Pei, Wei Qu, Hui Kong, Li Ouyang, Hong Mu, Lianshun Univ Chinese Acad Sci Beijing Peoples R China Chinese Acad Sci Inst Elect Engn Beijing Peoples R China State Grid Elect Power Res Inst Beijing Peoples R China

ISBN: (纸本)9781479914463;9781479914470

To improve the economic and environmental friendliness of the Microgrid(MG), this paper presents a comprehensive model to determine the distributed generation (DG) optimum output power, which can be formulated as a high-dimensional nonlinear constrained "black box" optimization problem. pattern search (PS)-an effective optimization algorithm is introduced to solve this optimization problem. Simulations are performed on the IEEE 13-node test feeder with various load profile, and comparisons are performed with other existing mature algorithms, the results have demonstrated the efficiency of the proposed approach.

关键词： Microgrid Economic Optimal Operation pattern search algorithm OpenDSS

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