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Ensemble Learning Model for Prediction of Natural Gas Spot Price Based on Least Squares Boosting Algorithm

Ensemble Learning Model for Prediction of Natural Gas Spot P...

2020 International Conference on Data Analytics for Business and Industry: Way Towards a Sustainable Economy, ICDABI 2020

作者： Ali, Aliyuda University of Sheffield Department of Automatic Control and Systems Engineering Sheffield United Kingdom

ISBN: (数字)9781728196756

ISBN: (纸本)9781728196756

Among fossil fuels, natural gas has been considered a fuel of choice for increasing the supply of energy and reducing environmental contamination worldwide. Given that the supply chain of natural gas is characterized by imbalances between demand and supply on a timely basis, effective and fast models for accurate spot price prediction for natural gas would not only inform but also help various stakeholders to make wise decisions in the competitive natural gas marketplace. Proposed in this paper is a regression ensemble learning model based on least squares boosting algorithm for improving the prediction of natural gas spot price on a monthly basis. Ensemble learning models are becoming more preferred predictive tools due to their capability to train multiple weak learning models, and aggregate their outputs to produce a strong learning model with better overall accuracy. A broad scope of time series data from January 1997 to May 2020 from Henry Hub natural gas spot prices were employed in developing and testing the proposed model. Coefficient of determination (R2), mean square error (MSE) and root mean square error (RMSE) are employed as performance metrics to evaluate the performance of the proposed model. Compared to four existing state-of-the-art approaches, overall results show that the proposed model exhibits better performance over the state-of-the-art methods with R2, MSE and RMSE scores of 0.9668, 0.3248, and 0.5699, respectively. © 2020 IEEE.

关键词： Learning systems

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Accurate TCP Position and Orientation Trajectory Generation in 6DOF Robotic Manipulators and CNC Machine Tools using FIR Filtering and Haversine Synchronisation

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Procedia CIRP 2023年 120卷 27-32页

作者： Rob Ward Burak Sencer Department of Automatic Control and Systems Engineering University of Sheffield Sheffield S1 3JD UK Advanced Manufacturing Research Centre University of Sheffield Rotherham S60 5TZ UK Mechanical Engineering Department Oregon State University Corvallis OR USA

The use of robotics in manufacturing is rapidly growing. One promising application in particular is the use of robots as machining platforms. Robotic machining offers many advantages such as large operating envelopes, flexibility in operations and low installation and running costs. Robotic machining platforms much like computer numerically controlled (CNC) machine tools are commanded by numerical controllers (NCs) using the well established G-code part programming language (ISO-6983). Toolpaths are defined in the work piece coordinate system (WCS) as a series of discrete tool centre point (TCP) positions and tool orientations. The role of the NC is to generate smooth feed drive or robot joint commands such that the tool or end effector travels along the commanded toolpath whilst satisfying TCP position and orientation tolerances and robot/machine tool kinematic constraints. Interpolating tool orientations directly in the WCS requires complex real-time spherical interpolation computations. Overcoming this challenge, this paper introduces a C 4 continuous tool path trajectory generation method for 6DOF motion. The tool centre point position is smoothed in the WCS, however, the tool orientation is smoothed directly in the rotary coordinate system without the requirement for spherical interpolation. The interpolated tool orientation trajectory follows the path of the great circle arc using the modified Haversine method eliminating non-linear interpolation errors present in linear interpolation of rotary axis positions (machine coordinate system interpolation). The proposed method is validated by simulation of a 6DOF robotic manipulator.

关键词： Robotic Machining interpolation Trajectory Generation Pose control Motion control

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Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT Analysis in Banjarmasin, Indonesia

Estimating Wind Energy Potential: Advanced Smart Hybrid VAWT...

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International Conference on Power engineering and Renewable Energy (ICPERE)

作者： Elysa Nensy Irawan Mei Miyagawa Maulana Putra Ken-Ichiro Yamashita Goro Fujita Functional Control Systems Shibaura Institute of Technology Tokyo Japan Department of Electrical Engineering Shibaura Institute of Technology Tokyo Japan Centre for Instrumentation Calibration and Engineering Indonesia Agency for Meteorology Climatology and Geophysics Jakarta Indonesia Department of Electrical Engineering Salesian Polytechnic Tokyo Japan

ISBN: (数字)9798331504694

ISBN: (纸本)9798331504700

This study explores the potential of smart hybrid Savonius-Darrieus wind turbines to optimize wind energy capture in Indonesia, a country with significant wind resources. With solar and wind energy leading the renewable energy transition, this research focuses on enhancing wind turbine efficiency in regions with variable wind speeds. The hybrid Savonius-Darrieus turbine integrates the complementary strengths of both turbine types, employing a solenoid mechanism to switch between modes and a filtering method to stabilize operation. Our results demonstrate that this innovative design significantly reduces mechanical wear and operational instability by minimizing unnecessary switching events. Testing in Banjarmasin, Indonesia, the daily average wind energy potential for the smart hybrid and conventional hybrid turbines is calculated to be 6.1 kWh and 4.7 kWh, respectively. This condition revealed that the smart hybrid turbine generates approximately 30.89% more power than conventional hybrid turbines, highlighting its superior adaptability to fluctuating wind conditions. The turbine's ability to maintain efficient energy capture across a wide range of wind speeds underscores its potential for broader application in diverse environmental settings.

关键词： Renewable energy sources Energy capture Wind energy Filtering Wind speed Switches Wind power generation Hybrid power systems Wind turbines Solenoids

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Transmissibility function analysis for the detection and localization of damage with nonlinear features in MDOF structural systems

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Structural Health Monitoring 2025年

作者： Cheng, Liangliang Lang, Ziqiang Cigada, Alfredo Zhu, Yunpeng Faculty of Science and Engineering University of Groningen Groningen Netherlands Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom Department of Mechanical Engineering Politecnico di Milano Milano Italy School of Engineering and Material Science Queen Mary University of London London United Kingdom

Transmissibility function analysis refers to the evaluation of the ratio between the spectra of two different outputs of a system and has been widely used for the detection and localization of damage in linear structural systems. In this article, a new transmissibility function analysis methodology is proposed to detect and localize damage with nonlinear features in multidegree-of-freedom (MDOF) structural systems. The methodology assumes the MDOF systems are subject to a general input with only the frequency range known a priori so is applicable to address damage detection and location issues for a wide range of engineering structures and systems. This methodology is derived based on the concept of nonlinear output frequency response functions (NOFRFs) and the concept of transmissibility of nonlinear systems introduced based on the NOFRFs. The transmissibility function analysis over output frequencies contributed by system nonlinearities is exploited to detect and localize damage with nonlinear features in MDOF structural systems. Both numerical simulations and experimental studies on a cracked beam structure in the laboratory have been conducted. The results verify the effectiveness and demonstrate the potential applications of the proposed methodology in the detection and localization of damage in practical engineering structures. © The Author(s) 2025.

关键词： damage detection dynamic system finite element method MDOF system Nonlinear output frequency response functions nonlinearity transmissibility

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Remote Microcontroller Scanner Design for STM32 Microcontrollers Used to Distance Education Form 20

Remote Microcontroller Scanner Design for STM32 Microcontrol...

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20th IEEE International Conference on Modern Electrical and Energy systems, MEES 2021

作者： Jacko, Patrik Guzan, Milan Kalinov, Andrii Technical University of Kosice FEI Department of Theoretical and Industrial Electrical Engineering Kosice Slovakia Kremenchuk Mykhailo Ostrohradskyi National University Systems of Automatic Control and Electric Drive Department Kremenchuk Ukraine

ISBN: (纸本)9781665423663

The novel coronavirus disease (Covid-19) is a global problem that has caused many changes in people's lives. One of the problems is distance education, that has caused a difficulty form of study. Students often do not have required study components, because they are in the home and teacher does not have complete control over them. This paper described remote control and monitor system for the microcontroller technique subject, where the teacher gets possibilities for monitoring each student's microcontroller program. The subject is focused to the basic peripherals and functionalities of STM32 microcontrollers and internet communication based on the ESP8266 chip. Therefore, the article contains of monitoring module design, remote control application and simple test of the remote-control scanner for STM32 microcontrollers focused to the distance form of study. © 2021 IEEE.

关键词： Remote control

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Leveraging GPT-4 Capabilities for Developing Context-Aware, Personalized Chatbot Interfaces in E-commerce Customer Support systems

Leveraging GPT-4 Capabilities for Developing Context-Aware, ...

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International Conference on Communications and Signal Processing

作者： Kathari Santosh Timur Kholmukhamedov M Sandeep Kumar Mohd Aarif Iskandar Muda B Kiran Bala Department of MBA CMR Institute of Technology Bengaluru Bengaluru India Automatic Control and Computer Engineering Department Turin Polytechnic University in Tashkent Tashkent Uzbekistan Publishing Global Research Network Noida India Universitas Sumatera Utara Medan Indonesia Department of Artificial Intelligence and Data Science K.Ramakrishnan college of Engineering Trichy

ISBN: (数字)9798350353068

ISBN: (纸本)9798350353075

In the realm of e-commerce customer support, the adoption of chatbots is on the rise, driven by a quest for heightened user interactions. This study introduces an inventive approach harnessing the advanced capabilities of GPT-4 to construct chatbot interfaces that are both context-aware and personalized. The main aim of this work is to revolutionize ecommerce customer support by developing intelligent and adaptable chatbot interfaces that are context-aware, personalized, and significantly enhance user experiences. Existing chatbot models struggle with context retention and personalization, limiting effectiveness in dynamic e-commerce environments despite the promise of automation. This innovative approach leverages GPT-4’s robust language processing, integrating it with user profiling systems for personalized responses grounded in user preferences and historical interactions. The method gives, diverse e-commerce dataset undergoes collection and pre-processing, followed by fine-tuning GPT-4 with an emphasis on context-awareness and personalized responses. The model is seamlessly integrated with e-commerce backend systems for real-time information, multimodal input support caters to varied user preferences. Results exhibit a significant 95% accuracy improvement, affirming the chatbot’s enhanced ability to comprehend user queries. By integrating personalization and advanced context retention, this study enhances user engagement, paving way for revolutionary intelligent and adaptable chatbot interfaces in ecommerce customer support.

关键词： Ethics Limiting Automation Biological system modeling Customer services Companies Chatbots

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Adaptive Fuzzy Fault-Tolerant control Using Nussbaum Gain for a Class of SISO Nonlinear systems with Unknown Directions 4th

Adaptive Fuzzy Fault-Tolerant Control Using Nussbaum Gain fo...

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4th International Conference on Electrical engineering and control Applications, ICEECA 2019

作者： Bounemeur, Abdelhamid chemachema, Mohamed Zahaf, Abdelmalek Bououden, Sofiane Laboratory of Automatic Robotic and Control Systems Faculty of Engineering Department of Electronics University of Constantine 1 Constantine Algeria Faculty of Sciences and Technology University Abbes Laghrour Khenchela Algeria

ISBN: (纸本)9789811564024

This paper treatsan indirect adaptive fuzzy fault-tolerant control using fuzzy systems for a class of uncertain SISO systems with unknown control gain sign and actuator faults. The uncertain nonlinearities of the systems and the actuator faults are approximated by fuzzy systems that have been proven to be universal approximators and the Nussbaum-type function is used to deal with the unknown control gain sign. The proposed control scheme completely overcomes the singularity problem that occurs in the indirect adaptive feedback linearizing control. Projection in the estimate parameters is not required and the stability analysis of the closed-loop system is performed using Lyapunov approach. Simulation results are provided to verify the effectiveness of the proposed design. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Nonlinear systems

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Distributed algorithms for solving the convex feasibility problems

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Science China(Information Sciences) 2020年第8期63卷 242-244页

作者： Kaihong LU Gangshan JING Long WANG Center for Complex Systems School of Mechano-electronic EngineeringXidian University Department of Applied Mathematics Hong Kong Polytechnic University Center for Systems and Control College of EngineeringPeking University

Dear editor,Along with the recent adoption of multi-agent networks [1–9], consensus-based distributed optimization has been extensively investigated. In [1], a distributed algorithm that combines the consensus and subgradient algorithms was developed for obtaining the solution of the unconstrained convex distributed optimization problems. In [2], a distributed discrete-time projected subgradient al-

关键词： Multi-agent systems Consensus Convex inequalities Subgradient Projection

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Machine learning for predicting energy efficiency of buildings: a small data approach

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Procedia Computer Science 2024年 231卷 72-77页

作者： Ivan Izonin Roman Tkachenko Stergios Aristoteles Mitoulis Asaad Faramarzi Ivan Tsmots Danylo Mashtalir Department of Artificial Intelligence Lviv Polytechnic National University Kniazia Romana str. 5 Lviv 79905 Ukraine Department of Civil Engineering School of Engineering University of Birmingham Birmingham B15 2TT United Kingdom Department of Publishing Information Technologies Lviv Polytechnic National University S. Bandera str. 12 Lviv 79013 Ukraine Department of Automated Control Systems Lviv Polytechnic National University Kniazia Romana str. 5 Lviv 79905 Ukraine

This paper provides a method for predicting the energy efficiency of buildings using artificial intelligence tools. The scopes is twofold: prediction of the levels of the heating load and cooling load of buildings. A feature of this research is the performance of intellectual analysis in conditions of a limited amount of data when solving the stated tasks. An improved method of augmentation and prediction (input-doubling method) is proposed by processing data within each cluster of the studied dataset. The selection of the latter occurs due to the use of the fast and easy-to-implement k-means method. Next, a prediction is made using the input-doubling method within each separate cluster. The simulation of the method was performed on a real-world dataset of 768 observations. The proposed approach was found to have a high prediction accuracy in the absence of overfitting and high generalization properties of the improved method. Comparison with existing methods showed an increase in accuracy by 40-46% (MSE) compared to SVR with rbf kernel, which is the basis for the improved method, and by 5-12% (MSE) compared to the closest existing hierarchical predictor.

关键词： artificial intelligence civil engineering energy efficiency small data approach prediction clustering input-doubling method

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Algorithm for Path Planning of Mobile Robot 24

Algorithm for Path Planning of Mobile Robot

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24th International Conference on Soft Computing and Measurements, SCM 2021

作者： Das, Nimai Chandra Uddin, Raihan Haque Zim, Md. Ziaul Skakun, Anastasiia D. Department of Automatic Control Systems Saint-Petersburg Electrotechnical University Leti Saint Petersburg Russia Daffodil International University Department of Software Engineering Dhaka Bangladesh Daffodil International University Department of Computer Science and Engineering Dhaka Bangladesh

ISBN: (纸本)9781665439749

Research in Unmanned Surface Vehicles (USVs) and Autonomous Mobile Robots navigation has demonstrated some success in navigating flat indoor environments while avoiding obstacles. But in common resilience to unsafe conditions, unmanned surface vehicles (USVs) and autonomous mobile robots have wide applications in security reconnaissance, investigation of an obscure domain, and crisis reaction. Various examinations have been directed on the driving mechanism, motion planning, and trajectory tracking strategies for robots, yet restricted investigations have been led with respect to the obstacle detection and avoiding ability of robots. However, for little scale robots that contain sensitive surveillance sensors and can't afford to utilize heavy defensive shells, the nonappearance of obstacle avoidance solutions arrangements would leave the robot helpless before possibly risky hindrances. In this paper, we present an algorithm for obstacle detection and avoidance system has been developed for miniature Unmanned Surface Vehicles (USVs) and autonomous mobile robots. We show an investigation differentiating heading build rules and relative course directions dodging distinctive operators in multi-specialist conditions, estimating separation between the two robots. The integration of distance measurement and avoiding other robots or obstacles is our observation in a multi-robot environment, where obstacles are also available. In this paper, we have discussed two algorithms, one will try to avoid other robot or obstacles and another will try to measure the distance between main agents to another agent. It utilizes an algorithm so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle. Therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance

关键词： Multi agent systems

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