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检索条件"任意字段=7th International Conference on Functional Programming"

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Extractive Single Document Summarization Using an Archive-Based Micro Genetic-2

Extractive Single Document Summarization Using an Archive-Ba...

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international conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Dipanwita Debnath Ranjita Das Partha Pakray Computer Science & Engineering National Institute of Technology Mizoram Mizoram India Computer Science & Engineering National Institute of Technology Silchar Assam India

ISBN: (数字)9781728175591

ISBN: (纸本)9781728175607

Research on automatic text summarization is growing with the rapid growth of online information services. In the current study, Extractive Single Document Summarization (ESDS) is formulated as a multi-objective optimization problem, and an Archive-based Micro Genetic-2 Algorithm (AMGA2) is employed to solve this problem. In this approach, each summary is represented in a binary form. the initial population is created using the clustering and Latin Hypercube (LH) sampling, resulting in a good overall unbiased population distribution in the genotypic space. Two objective functions were formed considering content coverage and informativeness as objective function 1, and anti-redundancy as objective function 2. the summary length limit is considered as the constraint. For generating offspring, an archive-based mating pool and modified mutation operator of differential evaluation are used. Finally, from the optimal set of solutions, the best solution is selected to generate the summary. For evaluation, DUC-2001 and DUC-2002 datasets are utilized, and the obtained results are compared with various existing methods using ROUGE measures. the obtained result illustrates the superiority of our approach in terms of convergence rate and ROUGE scores.

关键词： Statistics Sociology Optimization Linear programming Feature extraction Electrostatic discharges Genetic algorithms

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App making for pro-social and environmental change at an equity-oriented makeathon 17

App making for pro-social and environmental change at an equ...

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7th Annual conference on Creativity and Making in Education, FabLearn 2017

作者： MacDowell, Paula Ralph, Rachel Ng, David Simon Fraser University 250 - 13450 102 Avenue SurreyBCV3T 0A3 Canada University of British Columbia 2125 Main Mall VancouverBCV6T 1Z4 Canada University of British Columbia 300-2185 East Mall VancouverBCV6T 1Z4 Canada

ISBN: (纸本)9781450363495

the purpose of this paper is to analyze the effectiveness of an equity-oriented Makeathon designed to foster maker mindsets and maker identities in high school girls by engaging them with diverse tools, materials, mentorship, collaborative prototyping, and creative computing. the central theme of the University of British Columbia (UBC) Girls' Makeathon emphasized Tech for Change. Teams were challenged to make a mobile app related to an issue that teen girls face in local or global communities throughout the world. Participants learned how to identify a complex problem, design effective solutions, and change the world for the better by communicating their ideas (via apps and a pitch to a panel of experts). the results from the girls' design experiences, team presentations, surveys, and interviews show gains in their understandings of greening making and pro-social change making. Findings underscore the matter concerning how, why, and where do girls learn to become makers, coders, and inventors of media and technology (thereby overturning traditional gender and generational stereotypes)? the lessons learned in empowering girls to tackle inequality and create the futures they want to be part of will be useful for teachers and researchers who are interested in working with youth to design apps and innovative maker activities for environmental and sustainable education, research, and/or outreach. © 2017 Copyright held by the owner/author(s).

关键词： Computer programming

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Surrogate Optimization of Compensating Magnetic Dipoles Placement for Unmanned Underwater Vehicle

Surrogate Optimization of Compensating Magnetic Dipoles Plac...

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IEEE international conference on Actual Problems of Unmanned Air Vehicles Developments Proceedings (APUAVD)

作者： B. Kuznetsov T. Nikitina I. Bovdui K. Chunikhin department of magnetism of technical objects Anatolii Pidhornyi Institute of Power Machines and Systems of the National Academy of Sciences of Ukraine Kharkiv Ukraine Educational scientific professional pedagogical Institute V.N. Karazin Kharkiv National University Bakhmut Ukraine

ISBN: (数字)9798331534141

ISBN: (纸本)9798331534158

the method for reduction of magnetic field (MF) of uncertain unmanned underwater vehicle (UUV) based on surrogate optimization of compensating magnetic dipoles (CMD) to compensate of spheroidal harmonics of external MF developed. Spatial arrangement coordinates and spherical harmonics (SH) magnitudes of CMD calculated as geometric inverse magneto statics problems (GIMSP) solution in nonlinear minimax optimization problem (NMMOP) form based on multyspheroidal MF model of UUV. Nonlinear objective function (NOF) calculated as resulting MF weighted squared sum by COMSOL Multiphysics software package used. NMMOP solutions calculated based on particle swarm nonlinear optimization (PSNO) algorithms. Possibility to reduce by almost 100 times of MF induction (MFI) modulus and horizontal component of uncertain UUV based on surrogate optimization of CMD spatial arrangement for compensate of spheroidal harmonics of external MF using multyspheroidal model of MF of UUV shown.

关键词： Autonomous underwater vehicles Software packages Simulation Software algorithms Harmonic analysis Linear programming Autonomous aerial vehicles Magnetic fields Particle swarm optimization Optimization

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Optimal Design of Group Orthogonal MIMO Radar Waveforms Bases on Quantum Genetic Algorithm

Optimal Design of Group Orthogonal MIMO Radar Waveforms Base...

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IEEE international conference on Information Communication and Signal Processing (ICICSP)

作者： Zhimin Qu Hongbo Zhang Tianqu Liu Jinping Sun School of Electronic and Information Engineering Beihang University Beijing China School of Automation SouthEast University Nanjing China AVIC Leihua Electronic Technology Research Institute Wuxi China

ISBN: (数字)9798350355895

ISBN: (纸本)9798350355901

Digital radio frequency memory (DRFM) devices can quickly intercept radar waveforms and has become the main technique to achieve advanced radar jamming. Multiple-input multiple-output (MIMO) radars can counter advanced DRFM jamming based on waveform agility technology by emitting waveform sets which are orthogonal between groups. To design multiple groups of orthogonal waveform sets simultaneously, an optimization design model for group agile orthogonal waveform sets is developed in this paper. the correlation function peak of intergroup waveforms is multiplied by a deviation weight, serving as the objective function. In order to solve the proposed optimization model, we propose an optimization design algorithm for group agile orthogonal waveform sets. the quantum genetic algorithm (QGA), employing a partial search strategy and having no special requirements on the properties of the objective function, is capable of solving such complex non-convex optimization problems. Numerical simulation results demonstrate that the proposed algorithm yields waveform sets with good intra- and intergroup orthogonality performance, adjustable via changing weight coefficients.

关键词： Correlation MIMO radar Simulation Signal processing algorithms Radar Signal processing Linear programming Jamming Optimization Genetic algorithms

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Distributed Robust Optimization-Based Coordinated Day-Ahead Scheduling Method for Distribution-Microgrid Coordination

Distributed Robust Optimization-Based Coordinated Day-Ahead ...

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China international Electrical and Energy conference (CIEEC)

作者： Han Zhentao Wang Qixiang Zhang Mingli Han Liu Wang Jing Yu Zongmin State Grid Liaoning Electric Power Company Limited Economic Research Institute Shenyang China State Grid Liaoning Electric Power Co. Ltd. Shenyang China State Grid Economic and Technological Research Institute Co. Ltd. Beijing China Sichuan Energy Internet Research Institute Tsinghua University Chengdu China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Microgrids are essential for integrating new energy sources and enhancing distribution network reliability. Coordination among multiple microgrids is crucial for safe and economic operation. Coordinated dispatching requires a distributed approach considering uncertainties in new energy sources and discrete control devices. the method employs distributed robust optimization for uncertainty representation and the SDM-GS-ALM algorithm for discrete control. It approximates integer variables through convex hulls, ensuring convexity. the C&CG algorithm serves as the outer layer, embedding SDM-GS-ALM in various stages. this establishes a framework for distributed computation in coordinating distribution and microgrids. the proposed method's effectiveness is validated using the North American 5-node system with Aggregate equivalent method for line operation state consideration.

关键词： System testing Uncertainty Processor scheduling Microgrids Approximation algorithms Scheduling Mixed integer linear programming

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Learning Ant Colony Algorithm for Solving Green Multi-Compartment Vehicle Routing Problem with Simultaneous Pickup and Delivery

Learning Ant Colony Algorithm for Solving Green Multi-Compar...

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IEEE international conference on Automation, Electronics and Electrical Engineering (AUTEEE)

作者： Yan Geng Ning Guo Bin Qian Information Engineering and Automation Institute Kunming University of Science and Technology Kunming China

ISBN: (数字)9798350377033

ISBN: (纸本)9798350377040

To solve the Green Multi-Compartment Vehicle Routing Problem with Simultaneous Pickup and Delivery (GMCVRPSPD), a mathematical model is established with the objective of minimizing total costs. the model consists of vehicle operating costs and fuel consumption costs. A Learning Ant Colony Optimization algorithm (LACO) is proposed to solve GMCVRPSPD. Firstly, in the global search stage of LACO, three different heuristic methods are used to generate the initial solution. these solutions are used to initialize the pheromone matrix, providing a better starting point for the algorithm's subsequent search process. A pheromone update mechanism is designed to effectively enhance the convergence speed of the algorithm. Secondly, in the local search of LACO: a local learning strategy is designed, which selects the neighborhood operation suitable for the current search stage from the six neighborhood operations designed, and dynamically updates the selection probability value according to the contribution value generated by the neighborhood operation. In addition, a rapid evaluation strategy is designed to reduce the calculation time in the local search process. Finally, the effectiveness of LACO in solving GMCVRPSPD problem is verified by simulation experiment and algorithm comparison.

关键词： Integer programming Ant colony optimization Costs Heuristic algorithms Vehicle routing Transportation Search problems Mathematical models Optimization Convergence

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Research and Analysis on Management Methods of Line Loss for High Permeability Distributed Photovoltaic Access Transformer District

Research and Analysis on Management Methods of Line Loss for...

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China international Electrical and Energy conference (CIEEC)

作者： Xin Wang Weishu Zheng Xuecheng Kong Guang Liu Chaochao Liang Haijin Zhang State Grid Shandong Electric Power Company Zibo Power Supply Company Zibo China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

Aiming at the problem of excessive line loss in high permeability distributed photovoltaic access transformer district, we proposed a line loss control method for distributed photovoltaic access transformer district based on the krill swarm algorithm. Firstly, the minimum objective function of active power loss and voltage offset at the node of photovoltaic access transformer district area is constructed, and the optimal solution of the objective function is obtained by using the improved krill swarm algorithm. Secondly, a high permeability distributed photovoltaic transformer district lumped total equivalent analysis model is established, besides, a coordinated control method for total active and reactive power output of photovoltaic that meets the optimal objective function is proposed. On the above basis, the cosine decreasing step evolution method is used to further optimize the improved krill swarm algorithm, and the optimal power allocation values for each distributed photovoltaic system in the transformer district were also obtained. Finally, a typical high permeability distributed photovoltaic transformer district area is selected for simulation and comparative analysis,proving that this line loss control method can achieve refined management of line losses in photovoltaic transformer district.

关键词： Photovoltaic systems Reactive power Transformers Linear programming Inverters Permeability Resource management

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Fixed-Time Distributed Optimization for Networked Multi-Agent Systems with Unknown Disturbances Over Signed Graph

Fixed-Time Distributed Optimization for Networked Multi-Agen...

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international conference on Electronics Technology (ICET)

作者： Xian Qing Kaiyu Qin Zhiqiang Li Mengji Shi Boxian Lin Yuehong Dai School of Aeronautics and Astronautics University of Electronic Science and Technology of China Chengdu China Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu China National Laboratory on Adaptive Optics Chengdu China

ISBN: (数字)9798350363951

ISBN: (纸本)9798350363968

In this paper, the distributed optimization problem for networked multi-agent systems with unknown disturbances over signed graph is addressed. A novel robust fixed-time distributed optimization scheme is proposed. this scheme is divided into two components: a distributed observer-based optimization algorithm and a robust tracking controller. the distributed observer-based optimization algorithm makes the virtual state of each agent achieve bipartite consensus in fixed-time and obtain the optimal solution of the global convex objective function under the signed graph. the robust tracking controller is designed to eliminate the effect of external bounded disturbance, so that the actual state of the agent converges to the virtual state. the distributed optimization scheme can suppress the disturbances and obtain the optimal solution, and the convergence time is independent of the initial values of agents. Finally, some simulation results are given to verify the proposed fixed-time distributed optimization scheme.

关键词： Upper bound Simulation Linear programming Delays Optimization Multi-agent systems Convergence

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Optimal Allocation of Second-use Energy Storage Capacity Considering the Attenuation of Available Capacity

Optimal Allocation of Second-use Energy Storage Capacity Con...

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Energy, Electrical and Power Engineering (CEEPE), international conference on

作者： Yuchao Xiong Tiangang Lv Yue Gao Chao Chen Fei Xia Jingtian Hu Liang Yu Three Gorges Electric Energy Co. Ltd. Wuhan China Wuhan Yangtze Daily Communication Co. Ltd Wuhan China Wuhan Foreign Languages School Wuhan China

ISBN: (数字)9798350375794

ISBN: (纸本)9798350375800

In existing research on the full life cycle allocation of second-use energy storage systems, historical data from typical days or longer time scales of power stations are often used as the response conditions for energy storage in certain scenarios, and the benefits brought to power stations during the full life cycle of energy storage are calculated accordingly. the actual available capacity of energy storage is continuously declining due to life decay during use, which has resulted in higher benefits during the full life cycle of energy storage, indirectly causing a low calculation of the full life cycle cost of energy storage. this article considers the increase in power stations costs caused by the full life cycle decay of energy storage available capacity, and builds a multi-objective optimization allocation model for second-use energy storage systems based on the background of energy storage tracking power generation plans. Genetic algorithm is used to solve the model, and the feasibility of the proposed model is verified.

关键词： Analytical models Costs Optimization models Predictive models Linear programming Resource management Power generation

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Optimizing the Generating Power of Generators with Hydrogen Generators in Mind

Optimizing the Generating Power of Generators with Hydrogen ...

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international conference on Green Technology and Sustainable Development (GTSD)

作者： Nguyen thi My Hien Trieu Tan Phung Nguyen Hoang Trung Huynh thi thu Hien Nguyen Ngoc Au Tran Van Nam Faculty of Electrical and Electronics Engineering HCMC University of Technology and Education Ho Chi Minh city Vietnam Electrical and Electronic Department Cao Thang Technical College Ho Chi Minh city Vietnam VNU High School for the gifted Ho Chi Minh city Vietnam

ISBN: (数字)9798350386073

ISBN: (纸本)9798350386080

the paper presents a method for determining the appropriate installed power capacity of generators to minimize fuel costs in the power grid, taking into account the integration of hydrogen power sources. Specifically, the paper develops a cost function that considers some factors about the power sources within the IEEE 30-Bus power grid. Additionally, issues related to electricity prices during off-peak, normal, and peak periods are considered in formulating the objective function. Consequently, a cost function is developed that takes the combination of hydrogen generators into consideration. through the use of the Particle Swarm Optimization (PSO) algorithm, the minimum generated power required to optimize the power system's operation is determined. Simulation results demonstrate the feasibility of this approach and its effectiveness in reducing the operation costs of power plants, thereby enhancing grid efficiency and lowering the production costs of electrical energy for the power plant.

关键词： Costs Hydrogen Propagation losses Linear programming Cost function Generators Power grids

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