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检索条件"任意字段=18th International Conference on Logic Programming"

共 3127 条记录，以下是3021-3030 订阅

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Modelling Wind Power Generation in Probabilistic Power Systems Analysis: A Case Study with Non-Gaussian Correlated Random Variables

Modelling Wind Power Generation in Probabilistic Power Syste...

引用

international conference on Probabilistic Methods Applied to Power Systems (PMAPS)

作者： José Francisco Moreira Pessanha Albert Cordeiro Geber Melo Maria Elvira Pineiro Maceira Mathematics and Statistics Institute UERJ - Rio de Janeiro State University Rio de Janeiro Brazil

ISBN: (数字)9798350372786

ISBN: (纸本)9798350372793

the rapid expansion of wind power generation demands an update to the computational tools used for decision-making in the operation and planning of electrical power systems. this paper presents a methodology for modeling spatial correlations among wind speeds in probabilistic power system analysis. the approach employs the Nataf transformation and Monte Carlo Simulation. Additionally, the stochastic connection between wind speed and wind power is modeled using a conditional quantile copula kernel density estimator. the methodology is demonstrated through case studies involving the modified IEEE 24-Bus Test System and the Brazilian Northeast Power System, a real-world system with 965 buses.

关键词： Correlation Uncertainty Monte Carlo methods Wind speed Stochastic processes Wind power generation Probabilistic logic

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UAV Cooperative Air Combat Maneuvering Decision-Making Using GRU-MAPPO

UAV Cooperative Air Combat Maneuvering Decision-Making Using...

引用

international conference on Control and Automation (ICCA)

作者： Caiyi Chen Zhengyu Guo Delin Luo Yang Xu Haibin Duan School of Aerospace Engineering Xiamen University Xiamen China National Key Laboratory of Air-based Information Perception and Fusion Luoyang China School of Civil Aviation Northwestern Polytechnical University Xian China School of Automation Science and Electrical Engineering Beihang University Beijing China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this article, a GRU-Multi-agent Proximal Policy Optimization (GRU-MAPPO) algorithm was proposed to address unmanned aerial vehicle (UAV) cooperative air combat decision-making problem. this algorithm adds a layer of GRU to the Actor-Critic network framework, uses update gate to extract the historical temporal information and enhance situational awareness. Finally, experiments in our constructed UAV cooperative air combat environment demonstrate that UAVs using the algorithm proposed in this article can learn effective strategies in air combat environments and achieve high win rates.

关键词： Training Automation Atmospheric modeling Decision making Neural networks logic gates Autonomous aerial vehicles

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A Risk Assessment Based Method for Prioritizing Power Substation Apparatus Maintenances

A Risk Assessment Based Method for Prioritizing Power Substa...

引用

international conference on Probabilistic Methods Applied to Power Systems (PMAPS)

作者： Nan Zhou Yan Xu Sungin Cho Cheng Tian Wee Lingfeng Luo School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Singapore Power Group Singapore Singapore

ISBN: (数字)9798350372786

ISBN: (纸本)9798350372793

Proper planning for apparatus maintenance is of great importance to a power utility for maintaining power grid reliability while optimizing the resources. In this paper, a risk assessment-based method is proposed to prioritize power substation apparatus for maintenance. Firstly, a probabilistic failure model is developed for both power transformers and switchgears with the historical failure data. Secondly, the service of each apparatus is substituted into the failure model to derive the failure probability. Finally, the total risk including the maintenance cost, load curtailment cost, and failure risk are calculated with the failure probability, which is then utilized to derive the maintenance priority. Case studies are performed using historical data of low-voltage power apparatus in Singapore power grid.

关键词： Substations Costs Probability Probabilistic logic Power grids Data models Maintenance

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Keeping Information Alive: Hovering Information and Floating Content Paradigms for Vehicular Networks

Keeping Information Alive: Hovering Information and Floating...

引用

international conference on Distributed Computing in Sensor Systems (DCOSS)

作者： Lachlan Johnston Richard W. Pazzi Faculty of Business and Information Technology Ontario Tech University Canada

ISBN: (数字)9781665495127

ISBN: (纸本)9781665495134

Hovering Information and Floating Content are two sub-domains of information dissemination which aim to keep information persistent in a region where vehicle to vehicle (V2V) communication is the only option. In this mutual goal to keep information alive, both sub-domains have sought to design algorithms that overcome the geographical and technological challenges while maintaining efficient resource management. Techniques have arising which stem from flooding and broadcasting techniques, probabilistic communication, and using machine learning to direct communication. this work will examine the state-of-the-art works within both sub-domains to bring the reader to a respectable level of knowledge, and offer insight into the future directions research in the area may take.

关键词： Machine learning algorithms Heuristic algorithms Vehicular ad hoc networks Machine learning Predictive models Probabilistic logic Prediction algorithms

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Multi-Objective Derivative-Free Optimization Based on Hessian-Aware Gaussian Smoothing Method

Multi-Objective Derivative-Free Optimization Based on Hessia...

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international conference on Control and Automation (ICCA)

作者： Ran Chen Yuzhe Li Tianyou Chai State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

Most deterministic multi-objective optimization algorithms assume that the analytical objective functions and multi-objective gradients are available. However, there may be no available or explicit mathematical model for many real-world optimization problems. these problems are difficult to handle since the evaluations of gradients are inexact or even infeasible, which are termed derivative-free (or zeroth-order) optimization problems. To tackle the issues, a multi-objective derivative-free optimization based on Hessian-aware Gaussian smoothing method is proposed. We evaluate the multi-objective descent direction and produce new candidates for searching the Pareto front. Furthermore, we analyze the corresponding convergence rate of candidates produced by the Hessian-aware Gaussian smoothing method explicitly. Finally, we compared different multi-objective optimization algorithms and illustrated their performance on numerical benchmarks to show the proposed algorithm's effectiveness.

关键词： Measurement Sufficient conditions Smoothing methods Heuristic algorithms Estimation Approximation algorithms Linear programming

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Multi-objective Optimisation of Dynamic Responses for a Rail Freight Wagon using Regression Models

Multi-objective Optimisation of Dynamic Responses for a Rail...

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IEEE international conference on Cognitive Informatics

作者： Manish Pandey Rituparna Datta Rajarshi Dey Bishakh Bhattacharya Research Designs and Standards Organisation Lucknow India University of South Alabama Indian Institute of Technology Kanpur India

ISBN: (数字)9781728114194

ISBN: (纸本)9781728104966

the optimization problem of the carbody dynamic response for a freight wagon fitted with three-piece bogie can be formulated as a multi-objective optimisation problem wherein four of the dynamic response parameters i.e. vertical acceleration on straight track in empty and loaded condition, lateral acceleration on 2° curve in empty and loaded condition, may be selected as representative objective functions for the overall dynamic response of the freight wagon. In this paper, attempts are made to form non-linear regression equations with experimental data to formulate the objective functions. After that, computational intelligence based evolutionary multi-objective optimisation is used to solve the problem and Pareto fronts are drawn for the objective functions using NSGA-II. Subsequently, the weighted optimization problem is solved for a different combination of weights.

关键词： Optimization Linear programming Acceleration Mathematical model Computational intelligence Standards Computer science

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PTC-FOZNN: A Strictly Predefined-Time Convergent Fractional-Order Recurrent Neural Network for Solving Time-Variant Quadratic programming

PTC-FOZNN: A Strictly Predefined-Time Convergent Fractional-...

引用

international conference on Control and Automation (ICCA)

作者： Yi Yang Weibing Li Jianshu Zhou Junda Huang Jinfei Hu Richard M. Voyles Xin Ma Department of Mechanical and Automation Engineering Multi-Scale Medical Robotics Center The Chinese University of Hong Kong Hong Kong China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong China School of Engineering Technology Purdue University West Lafayette IN USA

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

this study presents a Predefined-Time Convergent Fractional-Order Zeroing Neural Network (PTC-FOZNN) as an innovative solution for Time-Invariant Quadratic programming (TIQP) and Time-Variant Quadratic programming (TVQP) problems. this model represents a noteworthy integration of fractional calculus into recurrent neural networks for cyclic motion planning of robots. the PTC-FOZNN diverges from the conventional Zeroing Neural Network (ZNN) by implementing a conformable fractional derivative that complies with the Leibniz rule-a standard often unmet by existing fractional derivatives. Additionally, it employs a novel predefined-time stabilizer as its activation function. When compared to the traditional ZNN, the PTC-FOZNN, configured with $0 < \alpha\leq 1$ , exhibits enhanced convergence speed and greater positional accuracy for both TIQP and TVQP tasks. through meticulous theoretical and empirical validation, including simulation trials with a Franka Emika Panda robotic arm, the PTC-FOZNN model has proven its effectiveness in precise trajectory tracking and computational efficacy.

关键词： Recurrent neural networks Trajectory tracking Kinematics Manipulators Planning Quadratic programming Task analysis

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Distributed Online Optimization Based on One-Step Gradient Descent and Multi-Step Consensus

Distributed Online Optimization Based on One-Step Gradient D...

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international conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Yingjie Zhou Xinyu Wang Tao Li School of Mathematical Sciences East China Normal University Shanghai China Shenzhen Baimai Technology Co. Ltd. Shenzhen China Ministry of Education Key Laboratory of Mathematics and Engineering Applications China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

We propose a distributed online optimization al-gorithm with continuously learning ability. In this algorithm, we first perform one-step gradient descent with fixed step size to ensure the ability of tracking the optimal solutions, and then use multi-step consensus to ensure the collaboration between neighboring nodes. For strongly convex and smooth objective functions, we provide a dynamic regret analysis of the proposed algorithm and show that the dynamic regret is upper bounded by the initial values, the path variation of the optimal solution, and a linear growth term. the coefficient of the linear growth term can be made arbitrarily small by adjusting the step size of gradient descent. We also demonstrate the performance of the proposed algorithm by numerical simulations.

关键词： Automation Heuristic algorithms Collaboration Numerical simulation Linear programming Optimization Robots

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A multi-bit error tolerant register file for a high reliable embedded processor

A multi-bit error tolerant register file for a high reliable...

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IEEE international conference on Electronics, Circuits and Systems (ICECS)

作者： Siamak Esmaeeli Morteza Hosseini Bijan Vosoughi Vahdat Bizhan Rashidian Department of Electrical Engineering Sharif University of Technology Tehran Iran

the vulnerability of microprocessors to soft errors is increasing due to continuous shrinking in fabrication process. Recent studies show that 1-5% of the SEUs (single event upset) can cause MBUs (multiple bit upsets). the probability of MBU generation due to SEU is increasing because of the reduction in minimum energy required to flip a memory bit in modern technologies. Register file is the most sensitive component in a microprocessor. In this paper, we present an innovative way to protect registers in a 64-bit register file for a RISC processor using extended Hamming (8, 4) code (SEC-DED code) and narrow-width values. A narrow-width value can be represented by half number of bits of the register width. Two additional bits for each data register have been used to store the information for a narrow-width value. Each 64-bit data in register file has its unique 64-bit extended Hamming code that is stored in another register file in a bit-interleaved manner. Two copies of narrow-width values can be stored in one register and each copy has its unique extended Hamming code in other register file. Proposed method has been tested using fault injection simulation with SPEC2000 benchmarks. Error probability of a word that stores generated values for register file in SPEC2000 benchmarks and is protected with proposed method is less than the error probability of the same word that is protected with TMR or various extended Hamming codes. the implementation on a Xilinx Virtex-4 FPGA shows that the area overhead of a register file with 64-bit wide and more than 64-word entry that is protected with proposed method is less than the area overhead of the same register file that is protected with TMR. Error detection and correction is performed in parallel with execute stage to prevent performance degradation. More than 99% of errors in adjacent 32 bits in data or extended Hamming code registers can be corrected with the proposed method. Presented method employs pure combinational lo

关键词： Registers Decoding Microprocessors Error probability Tunneling magnetoresistance Benchmark testing logic gates

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An analytic framework for specifying and analyzing imprecise requirements 96

An analytic framework for specifying and analyzing imprecise...

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Proceedings of the 18th international conference on Software engineering

作者： Xiaoqing Frank Liu John Yen Department of Computer Science University of Missouri Rolla Missouri Department of Computer Science Texas A&M University College Station Texas

ISBN: (纸本)9780818672460

there are at least three challenges with requirements analysis. First, it needs to bridge informal requirements, which are often vague and imprecise, to formal specification methods. Second, requirements often conflict with each other. third, existing formal requirement specification methodologies are limited in supporting trade-off analysis between conflicting requirements and identifying the impact of a requirement change to the rest of the system. In this paper, an analytic framework is developed for the specification and analysis of imprecise requirements. In this framework, the elasticity of imprecise requirements is captured using fuzzy logic and the relationships between requirements are formally classified into four categories: conflicting, cooperative, mutually exclusive and irrelevant. this formal foundation facilitates the inference of relationships between requirements for detecting implicit conflicts, to assess the relative priorities of requirements for resolving conflicts, and to assess the effect of a requirement change.

关键词： formal specification informal requirements trade-off analysis systems analysis irrelevant requirements requirement change imprecise requirements specification conflict resolution requirements analysis implicit conflicts relative priorities formal specification methods cooperative requirements mutually exclusive requirements fuzzy logic conflicting requirements

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