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Research on Risk Prediction Model of Power Grid Marketing Project Based on Fuzzy Logic Regression

Research on Risk Prediction Model of Power Grid Marketing Pr...

引用

Electronics, Energy systems and Power engineering (EESPE), ieee international conference on

作者： Xiaoyin Ding Jie Shen Yingxuan Zheng Lili Huang State Grid Zhejiang Electric Power Co. Ltd Quzhou Power Supply Company Quzhou China State Grid Zhejiang Electric Power Co. Ltd Quzhou Power Supply Company Jiangshan China Zhejiang Huayun Information Technology Co. Ltd. Hangzhou China

ISBN: (数字)9798350389579

ISBN: (纸本)9798350389586

This study proposes an innovative risk prediction model for power grid marketing, aiming to more comprehensively analyze and evaluate the risk situation under the influence of multiple factors in the marketing process. First, the model uses the fuzzy logic system to construct a multi-dimensional factor evaluation system, and analyzes based on historical data to extract the key influencing factors in the power grid marketing process. These influencing factors not only include the volatility of electricity market prices and load demand, but also cover seasonal changes, customer demand types, and policy orientations. Subsequently, the regression analysis method is used to process and analyze the above key influencing factors and establish a mathematical model for predicting risk. The mathematical model represents the influence of different influencing factors on risk in the form of regression equations, and improves the accuracy of prediction to a certain extent. To verify the effectiveness and applicability of the model, this study simulates in the MATLAB environment, and evaluates the performance of the model in different scenarios through simulation analysis of multiple real power grid marketing cases. The simulation results show that the risk prediction model based on the combination of fuzzy logic and regression analysis constructed in this study has high prediction accuracy in practical applications, with an accuracy rate of more than 85%.

关键词： Fuzzy logic Analytical models Accuracy Uncertainty Simulation Predictive models Mathematical models Power grids Regression analysis Risk management

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Cooperative Multi-Target Tracking Based on Multi-Detection TPHD in MIMO-OFDM systems

Cooperative Multi-Target Tracking Based on Multi-Detection T...

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international conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chen Zhong Lan Tang Ying-Chang Liang School of Electronic Science and Engineering Nanjing University Nanjing China Center for Intelligent Networking and Communication (CINC) University of of Electronic Science and Technology of China Chendu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper presents a passive multiple trajectories tracking system with multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) signals transmitted by the base station (BS). Firstly, we propose a Bayesian learning method to obtain the coarse estimations of targets and clutter, which are utilized for trajectories tracking. Considering the potential for a target to generate multiple measurements in overlapping areas of sweeping beams and non-Poisson clutter, we extend the trajectory probability hypothesis density (TPHD) filter to multi-detection TPHD (MD-TPHD) filter with non-Poisson clutter and provide its Gaussian mixture implementation. Simulation results show the performance of the algorithm.

关键词： Learning systems Target tracking Trajectory tracking Simulation Filtering algorithms MIMO Trajectory Bayes methods Clutter Speech processing

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Fine-Tuned Yolo V-10X: Real-Time Object Detection for Autonomous Vehicles Under Multiple Weather Conditions

Fine-Tuned Yolo V-10X: Real-Time Object Detection for Autono...

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ieee SSD international Multi-conference on systems, Signals and Devices

作者： Safa Teboulbi Seifeddine Messaoud Mohamed Ali Hajjaji Mohamed Atri Abdellatif Mtibaa Higher Institute of Computer Sciences and Mathematics of Monastir Monastir University Monastir Tunisia Faculty of Sciences of Monastir Monastir University Monastir Tunisia Higher Institute of Applied Sciences and Technology of Sousse Sousse University Sousse Tunisia Computer Engineering Department College of Computer Science King Khalid University Abha Saudi Arabia Systems Integration & Emerging Energies Laboratory National Engineering School of Sfax Sfax University Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Detecting objects such as vehicles, buildings, pedestrians, and road signs is indispensable to advancing the concept of autonomous and self-driving cars. Furthermore, an autonomous vehicle (AV) must accurately detect its surrounding environment to operate reliably. Most object detection (OD) techniques perform adequately under typical weather conditions, including cloudy or sunny days. However, their efficiency decreases significantly when exposed to Adverse Weather Conditions (AWCs), including days with sandstorm, rain, fog or snow. Complex and computationally costly models are required to achieve high accuracy rates. In this study, we present an improved OD system in AWCs for autonomous vehicles (AVs) using the single-stage deep learning (DL) algorithm YOLO (You Only Look Once) version 10. To evaluate our system, Vehicle Detection in Adverse Weather Nature (DAWN) dataset is used. It comprises real-world images captured under various types of AWCs. The experimental findings confirm that the suggested method is effective and surpasses state-of-the-art OD approaches under AWCs.

关键词： YOLO Adaptation models Accuracy Rain Smart cities Snow Roads Real-time systems Reliability Meteorology

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Channel Modeling for Underwater Acoustic Communication systems Using Liquid State Machines with Reservoir Computing

Channel Modeling for Underwater Acoustic Communication Syste...

引用

Integrated Circuits and Communication systems (ICICACS), ieee international conference on

作者： Rana Veer Samara Sihman Bharattej R Ramy Read Hossain Divya S Natesan M R. Dhilipkumar Doctorate of Business Administration National Louis University FL USA Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical and Electronics Engineering Nitte Meenakshi Institute of Technology Bengaluru India Department of Aeronautical Engineering Dhanalakshmi Srinivasan College of Engineering and Technology Mamallapuram India Department of Electronics and Communication Engineering New Prince Shri Bhavani College of Engineering and Technology Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

In recent years, Underwater Acoustic Communication (UAC) system is defined as Acoustic Signals (AS) by which information between underwater devices exchanged. UAC environment faces several challenges including dispersion and multipath distortion due to nature of channel modeling for reservoir computing. Hence, this research proposes Liquid State Machine-based Reservoir Computing (LSM-RC) for channel modeling with fixed input data called a “liquid” reservoir for processing input signals. Initially, the data is collected from Watkins Marine Mammal Sound Database (WMMSD) to analyze human activities. After that, preprocessing is performed using Quadrature Phase Shift Keying (QPSK) modulation to generate continuous signals through amplifier circuit. A pretrained model, Liquid State Machine (LSM) is used for modulation recognition of input signal to produce output signal. For prediction, RC is used to memorize and produce network modulation features which are capable of forecasting large-scale systems in UAC. Finally, LSM-RC predicts UAC signals with enhanced robustness and adaptability in underwater environments. The proposed LSM-RC achieved superior performance in terms of Mean Absolute Error (MAE) (0.0270) and Mean Absolute Percentage Error (MAPE) (0.4320) when compared to existing Orthogonal Time-Frequency Space (OTFS).

关键词： Adaptation models Underwater communication Time-frequency analysis Liquids Computational modeling Reservoir computing Predictive models Underwater acoustics Integrated circuit modeling Quadrature phase shift keying

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Improvement of Fault Finding Techniques in Industrial Robots: Using Unsupervised Learning for Predictive Maintenance

Improvement of Fault Finding Techniques in Industrial Robots...

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international conference on Electrical, Computer and Communication engineering (ECCE)

作者： Mehedi Hasan Nahidul Hasan Hasib Md. Miraiz Hossain Department of Mechatronics and Industrial Engineering Chittagong University of Engineering and Technology(CUET) Chittagong Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

A detailed comparative analysis of various machine learning models for predictive maintenance in industrial robotic systems is conducted. The focus is on constructing accurate models to forecast industrial robot breakdowns, enabling timely repairs, and reducing downtime. Data from industrial robots is gathered, feature engineering is performed, and multiple machine learning models are analyzed using the Silhouette Score. The goal is to identify the most effective model for predictive maintenance, aligning with the need for optimal system performance.

关键词： Analytical models Service robots system performance Machine learning Predictive models Industrial robots Reliability engineering Data models Unsupervised learning Predictive maintenance

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Cooperative Planning Strategy of Rural Distribution Networks and Energy Storage

Cooperative Planning Strategy of Rural Distribution Networks...

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Smart Grid and Artificial Intelligence (SGAI), international conference on

作者： Jiayin Dong Lei Sun Jiaqi Wang School of Electrical Engineering and Automation Hefei University of Technology Hefei China

ISBN: (数字)9798331518806

ISBN: (纸本)9798331518813

How to efficiently accommodate scaled distributed resources and ensure the security and reliability of power systems is a major issue that the construction of rural distribution networks must face in the current and future periods. In this background, a cooperative optimization planning method of rural distribution networks and energy storage is proposed considering the coordination of agricultural facilities in this work. First, the characteristics of agricultural loads are analyzed and mathematical models of agricultural greenhouse loads, agricultural irrigation loads and agricultural production loads are built. Then, a coordinated optimization planning model for rural distribution networks and energy storage is proposed, aiming to minimize the sum of investment and operating costs as the objective function, and an effective solution method is designed. Finally, an improved ieee 33-bus system is employed as an example to verify the effectiveness of the proposed planning method.

关键词： Irrigation Costs Distribution networks Production Mathematical models Regulation Planning Optimization Energy storage Load modeling

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I Was Blind but Now I See: Implementing Vision-Enabled Dialogue in Social Robots 25

I Was Blind but Now I See: Implementing Vision-Enabled Dialo...

引用

ACM/ieee international conference on Human-Robot Interaction (HRI)

作者： Giulio Antonio Abbo Tony Belpaeme IDLab-AIRO Ghent University - imec Ghent Belgium

ISBN: (数字)9798350378931

ISBN: (纸本)9798350378948

In the rapidly evolving landscape of human-robot interaction, the integration of vision capabilities into conversational agents stands as a crucial advancement. This paper presents a ready-to-use implementation of a dialogue manager that leverages the latest progress in Large Language Models (e.g., GPT-4o mini) to enhance the traditional text-based prompts with real-time visual input. LLMs are used to interpret both textual prompts and visual stimuli, creating a more contextually aware conversational agent. The system's prompt engineering, incorporating dialogue with summarisation of the images, en-sures a balance between context preservation and computational efficiency. Six interactions with a Furhat robot powered by this system are reported, illustrating and discussing the results obtained. The system can be customised and is available as a stand-alone application, a Furhat robot implementation, and a ROS2 package.

关键词： Visualization Image resolution Limiting Large language models Machine vision Social robots Human-robot interaction Oral communication Real-time systems Prompt engineering

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Application of natural language processing in foreign language artificial intelligence translation system

Application of natural language processing in foreign langua...

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2024 international conference on Computer Application and Information Security, ICCAIS 2024

作者： Zhou, Wei Gao, Bei School of Foreign Studies Harbin Engineering University Heilongjiang Harbin150001 China Department of Foundational Courses Teaching East University of Heilongjiang Heilongjiang Harbin150066 China

ISBN: (纸本)9781510689312

Natural language processing (NLP) technology in foreign language translation systems is an important subject in computer science. However, due to the high complexity of NLP, the logical method of symbolic modeling is relatively difficult to achieve the expected progress. With the development of AI technology, especially the application of machine learning, there are better solutions to complex rules and illogical strictness. However, the traditional foreign language translation system is still unable to translate obscure sentences completely. The new translation system has significantly improved compared with the traditional model in terms of format conversion rate, language modification effect, translation accuracy, speed of translation, and translation quality. In a word, NLP technology plays an important role in foreign language translation systems. © The Authors.

关键词： Computer aided language translation

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Research on the Design of Grain collecting and Bagging Machine Based on 51 series Single chip Microcontroller

Research on the Design of Grain collecting and Bagging Machi...

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ieee Information technology and Mechatronics engineering conference (ITOEC)

作者： Tongbang Su Lang Ma Jiahao Zhang Zhanlong Cao Chao Dong Meihao Lv Peijie Qiu College of Science and Technology Hubei Institute of Automotive TechnologyUniversity Hubei China School of Mechanical Engineering Hubei Institute of Automotive Technology Hubei China Changchun University of Science and Technology Jilin China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

Grain harvest at the time of grain maturity, grain drying and dehydration after the collection and packaging and timely return to storage is particularly important, China's intensive tanning farms are mostly, the design of a new type of grain collection and bagging equipment to realize the rapid collection and packaging of grains. Using a combination of theoretical analysis and three-dimensional model construction method, the mechanical design scheme of grain collection and bagging machine is analyzed. According to the functional requirements of the device, the virtual prototype is built through SolidWorks, and the circuit control system is designed, and the three-dimensional model of the key mechanical parts is built through finite element analysis to simulate and analyze and strength check, and verify its reliability. The device design can meet the demand for rapid collection and bagging of grain, its structure is reasonable, simple operation, improve the efficiency of grain collection and bagging work, can better complete the setup work, has a certain application prospects and promotion value.

关键词： Solid modeling Analytical models Mechatronics Microcontrollers Prototypes Reliability engineering Integrated circuit modeling Integrated circuit reliability Information technology Bagging

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Integrated waveform design of ITS channel and radar communication

Integrated waveform design of ITS channel and radar communic...

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ieee Information technology and Mechatronics engineering conference (ITOEC)

作者： Xundi Zheng School of Marxism Hohai University Nanjing China Nanjing Medical University Nanjing China

ISBN: (数字)9798331529482

ISBN: (纸本)9798331529499

This article demonstrates the time-varying nature of time-frequency domain channels and the sparsity of time-delay Doppler domain channels through simulation. The concepts and formulas of ambiguity function, PAPR, and BER are given, and the basic principles and integrated system structure of OFDM modulation are introduced. The ambiguity function formula of OFDM signals is derived, and its ambiguity function is verified to be a pushpin type through simulation. The formula for PAPR of OFDM signal is given, and simulation shows that PAPR increases with the increase of subcarrier number M. Then, the basic principle and system structure of OTFS modulation were introduced, and the ambiguity function of OTFS signal was given based on OFDM signal. It was proved that the ambiguity function of OTFS signal is also a pushpin type, and the PAPR of OTFS signal was analyzed. Finally, the relationship between PAPR and symbol number N of OFDM and OTFS signals was demonstrated through simulation, as well as the BER of the two signals at different target speeds. The advantages and disadvantages of the two modulation methods were analyzed from the aspects of CP length and modulation and demodulation complexity.

关键词： Time-frequency analysis Mechatronics Channel estimation Symbols Peak to average power ratio Radar OFDM modulation Doppler effect Information technology Demodulation

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