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fuzzy logic algorithm in the planning and design of tourist attraction facilities

JOURNAL OF COMPUTATIONAL METHODS IN SCIENCES AND ENGINEERING 2025年第1期25卷 472-485页

作者： Hong, Lihua Dong, Tao Zhengzhou Profess Tech Inst Elect & Informat Zhengzhou Peoples R China Henan Univ Sci & Technol Sch Appl Engn 263 Kaiyuan Ave Luoyang 472000 Henan Peoples R China

To address the uncertainties and complexities inherent in planning and designing tourist attraction facilities-challenges that traditional methods struggle to manage-this study utilizes fuzzy logic (FL) algorithms within artificial intelligence (AI) technology. Focusing on the planning of first aid facilities at tourist attractions, the research develops an FL reasoning system. The system's performance is evaluated using mean squared error (MSE) and mean absolute error (MAE) as key indicators. Key data features can be extracted by preprocessing operations such as data cleaning and normalization on the collected historical data of tourist attractions, and the fuzzy sets and corresponding membership functions of input and output variables can be determined. A fuzzy rule library can be constructed using historical data and professional knowledge, and a fuzzy inference machine can be used to infer the fuzzy set of input variables based on fuzzy rules to obtain predicted results and perform deblurring transformation to output actual results. The research highlights the significant value of the FL system in optimizing the planning of emergency facilities in tourist attractions. The experiment demonstrated that the system achieved mean squared error (MSE) and mean absolute error (MAE) values of 1.90 and 1.10, respectively. These results underscore the system's strong applicability and effectiveness, providing a reliable tool for enhancing emergency planning and ensuring safety in high-traffic areas.

关键词： artificial intelligence fuzzy logic algorithm tourist attractions facility planning fuzzy reasoning

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Construction of Power Production Safety Risk Assessment System Based on fuzzy logic algorithm 4

Construction of Power Production Safety Risk Assessment Syst...

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4th IEEE International Conference on Mobile Networks and Wireless Communications, ICMNWC 2024

作者： Li, Lumin Liang, Gang Jia, Junqiang Xiaokaiti, Maihebubai Yang, Jian State Grid Xinjiang Information & Telecommunication Company Xinjiang Urumqi China

ISBN: (纸本)9798350352931

With the continuous expansion of power production scale, safety risk assessment has become a key issue to ensure the stable operation of the power system. To address this issue, this article proposes a power production safety risk assessment system based on fuzzy logic algorithm. Firstly, a fuzzy membership function is established to quantify risk indicators in response to the fuzziness and uncertainty factors present in the power production process. Subsequently, an evaluation model based on fuzzy reasoning is designed to comprehensively evaluate and weight analyze various risk factors. Finally, a corresponding evaluation system is developed to achieve real-time monitoring and early warning of safety risks in power production. Through experimental analysis of actual power production data, the results show that the accuracy of the fuzzy logic algorithm system in risk identification reaches 87.5%, and the average error in future risk prediction is 2.87. In the above data conclusions, the evaluation method based on fuzzy logic algorithm can effectively warn potential safety risks when processing complex risk information, and has significant advantages, which can provide strong support for the safety management of power production. © 2024 IEEE.

关键词： electricity production safety fuzzy logic algorithm risk assessment risk prediction

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Determining Average Error of Flank Wear in Turning Duplex Stainless Steel Using Canny's Edge Detection algorithm in Comparison with fuzzy logic algorithm 6

Determining Average Error of Flank Wear in Turning Duplex St...

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6th International Conference on Contemporary Computing and Informatics, IC3I 2023

作者： Vignesh, S. Senthil Pon Bommi, R.M. Saveetha School of Engineering SIMATS Department of ECE Chennai India

ISBN: (纸本)9798350304480

To obtain the average error of flank wear in turning Duplex Stainless Steel (DSS) using Canny's Edge Detection algorithm and compare it with fuzzy logic algorithm. The average error accuracy of flank wear is computed for Canny's Edge Detection algorithm and fuzzy logic algorithm separately and are categorized into Group 1 and Group 2 respectively, each consisting of 27 samples, providing a total sample size of 54. It was computed using *** with an enrollment ratio of one, an alpha error of 0.05, a G-power of 80%, and a confidence interval of 95%. The average error accuracy determined using the Novel Canny's Edge Detection algorithm (92.78%) is more accurate and statistically significant than the fuzzy logic algorithm (88.91 %) and the significance value obtained is p = 0.000 (p © 2023 IEEE.

关键词： Average Error Duplex Stainless Steel Flank Wear fuzzy logic algorithm Novel Canny's Edge Detection algorithm Quality of Life Turning

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Identification of Herbaceous Plants with Electronic Nose using fuzzy logic algorithm 5

Identification of Herbaceous Plants with Electronic Nose usi...

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5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

作者： Armada, Elijah G. Manlises, Cyrel O. Mapua University School of Electrical Electronics and Computer Engineering Manila1002 Philippines

ISBN: (纸本)9798350314694

Herbs produce non-woody stems and have many applications in medicine, food, and perfume products. We used an electronic nose system and a fuzzy logic algorithm to identify herbaceous plants in this study. The gases emitted by the plants were analyzed with the MQ sensors. The results were used with a fuzzy logic approach to identify the name of the plant. The performance of the prototype system was evaluated for Oregano, Spearmint, and Peppermint with 38/45 plant samples. The prototype showed an accuracy of 100% for identifying oregano, 73.33% for spearmint, and 80.00% for peppermint. The overall accuracy was 84.44%. © 2023 IEEE.

关键词： electronic nose system fuzzy logic algorithm herbaceous plants mq sensors oregano peppermint spearmint

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An Improved Droop Control for DC Microgrid Based on fuzzy logic algorithm 9

An Improved Droop Control for DC Microgrid Based on Fuzzy Lo...

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IEEE 9th International Conference on Power Electronics Systems and Applications (PESA)

作者： Xie, Hongbiao Cai, Fenghuang Jiang, Jiahui Chen, Weidong Fuzhou Univ Coll Elect Engn & Automat Fuzhou Peoples R China Qingdao Univ Coll Elect Engn Qingdao Peoples R China

ISBN: (纸本)9781665486682

To solve the problem of traditional droop control in a DC microgrid cannot meet both current equalization and voltage regulation requirements in load distribution due to the presence of line impedance. This work proposes a fuzzy logic-based improved droop control scheme and designs two fuzzy controllers for the current compensation and bus voltage compensation, respectively. To improve current equalization accuracy and DC bus voltage stability, voltage compensator and current compensator based on fuzzy logic algorithm are designed. Finally, a simulation platform of the DC microgrid with three phase-shifted full-bridge DC/DC converters as the main circuit topology is built in MATLAB/Simulink to verify the feasibility and effectiveness of the proposed control scheme.

关键词： DC microgrid droop control fuzzy logic algorithm

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Adaptive time delay control for cable-driven manipulators using fuzzy logic algorithm

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PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART I-JOURNAL OF SYSTEMS AND CONTROL ENGINEERING 2021年第6期235卷 898-913页

作者： Yan, Fei Wang, Yaoyao Ju, Feng Chen, Bai Wu, Hongtao Nanjing Univ Aeronaut & Astronaut Natl Key Lab Sci & Technol Helicopter Transmiss Nanjing 210016 Peoples R China Zhejiang Univ State Key Lab Fluid Power & Mech Syst Hangzhou Peoples R China

A new adaptive time delay estimation technique with sliding mode control method is proposed and investigated in this passage for cable-driven manipulators. Time delay estimation technique is an effective tool to compensate for unmodeled dynamics and unknown disturbance, and adaptive time delay estimation performs better due to its adaptive control gain. The proposed adaptive method is based on the fuzzy logic algorithm which has a great advantage in input-output mapping thank to its flexibility. Tuning procedure is addressed to reveal the implementation of the newly proposed algorithm. Moreover, the desired trajectory is taken as an input of adaptive algorithm and better control performance is obtained through this attempt. The proposed controller is ultimately uniformly bounded and proof using the Lyapunov method is provided. Finally, comparative experiments show the validity and effectiveness of the proposed controller.

关键词： Control theory adaptive control cable-driven manipulator time delay estimation fuzzy logic algorithm

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Investigation of enterprise economic management model based on fuzzy logic algorithm

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HELIYON 2023年第8期9卷

作者： Kang, Ziyi Zhao, Yongkang Kim, Dongjoo Woosuk Univ Grad Sch Dept Social Econ & Management Wanju Gun 55338 South Korea Woosuk Univ Grad Sch Phys Educ Wanju Gun 55338 South Korea

With the development of modern society and economy, modern business models have changed. Enterprise management is no longer the main function, which requires new management concepts to coordinate production and operation and create new management models. Corporate economic management is one of the main tasks of corporate governance. In order to improve corporate governance, the effective corporate economic evaluation model must be established. The advantage of fuzzy logic algorithm is that it can effectively express fuzzy data and is easy to understand, which is more transparent. The application of fuzzy logic algorithm in the research of enterprise economic management can fully reflect the advantages of fuzzy logic algorithm and improve enterprise governance. In this paper, the fuzzy logic algorithm was used to study the economic management model of enterprises. This paper first introduced the enterprise economic management model, including the definition, characteristics and shortcomings of the enterprise economic management model. The performance evaluation methods of enterprise economic management were introduced, including the clarity of performance evaluation objectives, the optimization of performance evaluation means and the feedback of performance evaluation results. Finally, the fuzzy logic algorithm was used to evaluate the performance of enterprise economic management, and the indicators and performance evaluation model of enterprise economic management were established. In the experimental part, the fuzzy logic algorithm was used to evaluate the economic management of four enterprises. The experimental results showed that Enterprise A had the highest ability to evaluate the economic management of enterprises, and the comprehensive evaluation result of economic management was above 0.9, so it had a very high enterprise economic management ability. The application of fuzzy logic to the study of enterprise economic management could directly show the advant

关键词： Economic management mode Enterprise economy fuzzy logic algorithm Performance evaluation of enterprise economic management

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A fuzzy logic algorithm derived mechatronic concept prototype for crop damage avoidance during eco-friendly eradication of intra-row weeds

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Artificial Intelligence in Agriculture 2020年第1期4卷 116-126页

作者： Satya Prakash Kumar V.K.Tewari Abhilash K.Chandel C.R.Mehta Brajesh Nare C.R.Chethan Kaustubh Mundhada Prateek Shrivastava Chanchal Gupta Smrutilipi Hota Indian Council of Agricultural Research(ICAR) Central Institute of Agricultural EngineeringBhopalIndia Indian Institute of Technology Kharagpur 721302India Biological Systems Engineering Washington State UniversityPullman 99164WAUSA ICAR-Central Potato Research Station Jalandhar 144026India ICAR-Directorate of Weed Research Jabalpur 482004India

Crop damage during the intra-row weed eradiation is one of the biggest challenges in intercultural agricultural *** available mechanical systems provide effective weeding but result in excess crop *** the other hand,chemical based systems have been raising serious environmental and food *** study presents development of a cost-effectivemechatronic prototype for intra-rowweeding *** primary focus was on incurring minimal crop *** system integrates time of flight and inductive sensing into fuzzy logic algorithm for electronic control of a four-bar linkage mechanism(FBLM).The crank of FBLM was connected to the vertical rotary weed control shaft with weeding *** crop sensing triggers the electronic control to laterally shift the control shaft away from crop,proportional to the forward speed and soil *** developed algorithm incorporates varied conditions of soil,forward speed,and plant spacing to calculate dynamic lateral shift speed(SRPM).The prototype was evaluated to determine the relationships between the operating conditions and electronic control ***,the plant damage was assessed under varied conditions of plant spacing,forward speeds,soil cone index,operational depth and electronic control *** derived SRPM was established as the ultimate governing factor for avoiding crop damage that varied significantlywith electronic response time and soil strength(P<0.05).Plant damage increased significantly under higher forward speeds and lower plant spacing(P<0.05).Preliminary field evaluation of the developed prototype showed a significant potential of this system for effective control on weeds(>65%)and crop damage(<25%).

关键词： Intra-row weed control Mechatronic prototype fuzzy logic algorithm Plant damage Weeding efficiency

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Estimation of the Ageing Condition of Oil-Filled Transformers Based on the Oil Parameters Using a Novel fuzzy logic algorithm 21st

Estimation of the Ageing Condition of Oil-Filled Transformer...

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21st International Symposium on High Voltage Engineering (ISH)

作者： Kinkeldey, Tobias Muenster, Tobias Werle, Peter Suwarno Haemel, Kai Preusel, Joerg Leibniz Univ Hannover Inst Elect Power Syst Schering Inst Div High Voltage Engn & Asset Management Hannover Germany Inst Technol Sch Elect Engn & Informat Bandung Indonesia GRIDINSPECT GmbH Feldatal Germany

ISBN: (纸本)9783030316761;9783030316754

The condition of the transformer insulation determines the remaining life of the transformer. Over the transformer service life, both liquid and solid insulation undergoes a continuous aging process under electrical, chemical, mechanical and thermal stresses. The insulating liquid of a transformer can be reconditioned or replaced;however, this is not the case for the cellulose insulation. Therefore, the condition of the paper insulation is the major factor for determining the aging status of a transformer. To assess the paper condition, the common method is to measure the degree of polymerization (DP) of the paper insulation as a significant parameter. This method is destructive as it requires a sample of paper from inside of the transformer. Therefore, it could not be applied for transformers in operation. There are several approaches to approximate the DP value without direct measurements of paper samples. This research presents an improved method based on a fuzzy logic system for the estimation of the DP based on dissolved gases and chemical parameters of the liquid insulation. The algorithm is developed to create the rules for the use of fuzzy sets based on the information gain extracted by the entropy of the laboratory measurement data. This algorithm employs entropy to examine the sample homogeneity. Entropy is a measure of information theory that can determine the dataset characteristics concerning impurity and homogeneity. The algorithm uses fuzzy sets of oil parameters like Acidity, Interfacial Tension (IFT), Carbon Dioxide (CO2) and Carbon Monoxide (CO) and the breakdown voltage (BDV) for determination of the DP value.

关键词： fuzzy logic algorithm DP value Paper ageing

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Analysis of fuzzy logic algorithm for Load Balancing in SDN 4

Analysis of Fuzzy Logic Algorithm for Load Balancing in SDN

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4th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI)

作者： Prakoso, Ian Agung Hertiana, Sofia Naning Dewanta, Favian Telkom Univ Sch Elect Engn Bandung Indonesia

ISBN: (纸本)9781665401517

Server Resource limitations are generally an obstacle affecting the quality of service (QoS) due to increased traffic levels. Therefore, Load Balancing is needed to manage service requests to the optimal application server. Software-Defined Network (SDN) has advantages in controlling the network which can be exploited with various load balancing strategies that are used to distribute traffic loads to improve overall system performance. The Performance for load balancing can be improved by selecting the server with minimum load using the fuzzy logic algorithm. Traditional load balancing lacked the usage of device state data. In this study, an SDN-based Server Load Balancing method using fuzzy logic methods has been performed. fuzzy algorithm successfully delivers HTTP requests to lowest load server based on Distribution Server Index. In the testing, the server load must be directed at the lowest server weight so that each server should not be overloaded. In testing with a request load ranging from 100 - 500, the fuzzy algorithm imposes more traffic distribution on the 3rd Server with the lowest server load. In the CPU usage test, the fuzzy logic algorithm has the lowest average value namely 39%. In the RAM usage test, the fuzzy logic algorithm has the lowest average value namely 54%. In the throughput test, the fuzzy logic algorithm has the highest average value namely 2KBps. The Fairness Index of fuzzy logic is 0.45 while Round Robin's fairness index is 0.99. Round Robin algorithm can outperform other algorithms in terms of Fairness Index, as the fairest algorithm.

关键词： Software Defined Network (SDN) Load Balancing fuzzy logic algorithm

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