检索结果-内蒙古大学图书馆

Comprehensive optimization of combined cooling, heating, and power hybrid renewable multienergy system based on enhanced implementation feasibility

引用

RENEWABLE ENERGY 2025年 245卷

作者： Zhao, Xiangming Liu, Yuan He, Maogang Guo, Jianxiang Qingdao Univ Technol Key Lab Ind Fluid Energy Conservat & Pollut Contro Minist Educ Qingdao 266000 Peoples R China Xi An Jiao Tong Univ Sch Energy & Power Engn Key Lab Thermofluid Sci & Engn MOE Xian 710049 Peoples R China

To promote the implementation of optimization schemes, a comprehensive optimization approach is proposed with the aim of enhancing the implementation feasibility of a combined cooling, heating, and power (CCHP) system based on optimization solutions. The proposed method not only focuses on optimizing objective functions but also considers the optimization characteristics of decision variables. A computational model for a multienergy CCHP hybrid system incorporating solar, biomass, and geothermal energy is established. The optimization objective functions include the net present value, fossil energy consumption, and carbon dioxide emissions. The objective function results show that the HV values of the original algorithm and the jointly improved algorithm differ by 4.4%, indicating that they have similar performance characteristics. Regarding decision variables, the results show that the standard deviations of the decision variable deviations increase by 42.2%. In addition, the Solow-Polasky diversity measure increases by 21.3%. The improved algorithm presented in this paper significantly enhances the feasibility and diversity of system configurations (decision variables) while minimally impacting the objective functions. Further simplification of the decision variables in the optimization plan provides simplified optimization solutions for construction and operational maintenance. Moreover, the standardization of decision variables facilitates enhanced coordination between construction teams and equipment suppliers.

关键词： Implementation feasibility Multienergy CCHP Renewable energy Optimization solutions Decision variables objective functions

来源：评论

学校读者我要写书评

暂无评论

A Swarm Intelligence-Based Path Selection for Low-Power and Lossy Networks

引用

IEEE ACCESS 2024年 12卷 117218-117255页

作者： Almutairi, Hanin Aljanah, Salem Zhang, Ning Univ Manchester Dept Comp Sci Manchester M13 9PL England Imam Mohammad Ibn Saud Islamic Univ IMSIU Coll Comp & Informat Sci Riyadh 11432 Saudi Arabia

In a Low-power and Lossy Network (LLN), owing to its unique characteristics, such as lossy channels, dynamically changing network topology and resource-constrained nodes, finding a global optimum path to deliver packets efficiently and reliably is a challenging task. Current path-finding solutions in LLNs often fall short in addressing the issue of finding a global optimum path based on a comprehensive set of factors that impact network performance. To address these challenges, there is a critical need for a new approach that can dynamically and intelligently optimise routing paths in real-time, considering the most important factors. This paper investigates how to obtain a global optimum path in real-time in LLNs. It critically analyses existing path-finding solutions designed for LLNs and identifies two aspects for improvement. The first one is to capture all the factors that may impact packet delivery reliability by using a greater set of routing metrics. The set of metrics not only measures packet delivery reliability, the level of control overhead and packet delivery delays, but also energy preservation for prolonging network lifetime. The second one is a novel Swarm Intelligence-based Path Selection (SIPaS) framework for finding a global optimum path based on the real-time values of the routing metrics. We have coded the framework into an Ant Colony objective Function (ACOF) equipped with multiple routing metrics seamlessly integrated into the Routing Protocol for LLNs (RPL). Simulation results indicate that the SIPaS framework outperforms related solutions significantly in terms of packet delivery ratio, energy preservation, network lifetime extension, and reduction of both delay and control overhead.

关键词： Reliability Measurement Linear programming Routing protocols Codes Real-time systems Ant colony optimization Low-power and lossy networks (LLNs) swarm intelligence (SI) ant colony optimisation (ACO) objective functions routing routing protocol for low-power and lossy networks (RPL)

来源：评论

学校读者我要写书评

暂无评论

Human-in-the-Loop Optimization of Wearable Robotic Devices to Improve Human-Robot Interaction: A Systematic Review

引用

IEEE TRANSACTIONS ON CYBERNETICS 2023年第12期53卷 7483-7496页

作者： Diaz, Maria Alejandra Voss, Matthias Dillen, Arnau Tassignon, Bruno Flynn, Louis Geeroms, Joost Meeusen, Romain Verstraten, Tom Babic, Jan Beckerle, Philipp De Pauw, Kevin Vrije Univ Brussel Human Physiol & Sports Physiotherapy Res Grp B-1050 Brussels Belgium Vrije Univ Brussel Brussels Human Robot Res Ctr B-1050 Brussels Belgium Friedrich Alexander Univ Erlangen Nurnberg Inst Autonomous Syst & Mechatron Dept Elect Engn D-91052 Erlangen Germany IMEC B-1050 Brussels Belgium Vrije Univ Brussel Robot & Multibody Mech Res Grp B-1050 Brussels Belgium Flanders Make B-1050 Brussels Belgium Jozef Stefan Inst Lab Neuromech & Biorobot Dept Automat Biocybernet & Robot Ljubljana 1000 Slovenia Univ Ljubljana Fac Elect Engn Ljubljana 1000 Slovenia Friedrich Alexander Univ Erlangen Nurnberg Dept Artificial Intelligence Biomed Engn D-91052 Erlangen Germany

This article presents a systematic review on wearable robotic devices that use human-in-the-loop optimization (HILO) strategies to improve human-robot interaction. A total of 46 HILO studies were identified and divided into upper and lower limb robotic devices. The main aspects from HILO were identified, reviewed, and classified in four areas: 1) human-machine systems;2) optimization methods;3) control strategies;and 4) experimental protocols. A variety of objective functions (physiological, biomechanical, and subjective), optimization strategies, and optimized control parameters configurations used in different control strategies are presented and analyzed. An overview of experimental protocols is provided, including metrics, tasks, and conditions tested. Moreover, the relevance given to training or adaptation periods was explored. We outline an HILO framework that includes current wearable robots, optimization strategies, objective functions, control strategies, and experimental protocols. We conclude by highlighting current research gaps and defining future directions to improve the development of advanced HILO strategies in upper and lower limb wearable robots.

关键词： Human-in-the-loop optimization (HILO) human-robot interaction objective functions optimization strategies user performance wearable robots

来源：评论

学校读者我要写书评

暂无评论

Exergy optimization of a multi-stage solar micro-cogeneration system

引用

IET RENEWABLE POWER GENERATION 2023年第2期17卷 217-228页

作者： Kallio, Sonja Siroux, Monica Strasbourg Univ INSA Strasbourg ICUBE Strasbourg France

This paper proposes a dynamic model of a solar-based micro-cogeneration system called photovoltaic-thermal (PVT) collector to perform a design optimization of the multi-stage PVT system. The parametric study reveals the most important design parameters influencing the water-based flat-plate PVT system performance. The analysis also shows an existing trade-off between thermal and electrical efficiencies during the PVT operation. A novel exergy-based multi-objective design optimization method is demonstrated to find a trade-off design solution of the multi-stage PVT collector which compromises between the electrical and thermal exergy efficiencies under different weather conditions. The electrical and thermal exergy efficiencies are defined to be the objective functions of the Matlab gamultiobj-function, which is a multi-objective evolutionary algorithm using non-dominated sorting genetic algorithm-II (NSGA-II). As a result of the algorithm, the Pareto optimal sets were derived that revealed the optimal solutions taking into account the trade-off nature of the optimization problem. The decision-making method called an ideal point method was used in the decision-making process to find the final optimal solutions for different weather conditions. The results revealed that the optimal number of the PVT collectors in series depended on the weather conditions and decreased from 3 to 2 if the conditions got cooler.

关键词： genetic algorithms Optimisation techniques water-based flat-plate PVT system performance trade-off nature objective functions Solar power stations and photovoltaic power systems multiobjective evolutionary algorithm dynamic model Pareto optimisation sorting genetic algorithm-II multistage PVT collector PVT collectors photovoltaic-thermal collector evolutionary computation optimization problem microcogeneration system final optimal solutions PVT operation solar absorber-convertors important design parameters electrical efficiencies multistage PVT system cogeneration novel exergy-based multiobjective design optimization method Other direct energy conversion optimal number existing trade electrical exergy efficiencies thermal exergy efficiencies exergy Optimisation decision-making method exergy optimization decision making trade-off design solution optimisation Pareto optimal sets

来源：评论

学校读者我要写书评

暂无评论

Developing a real-time self-organizing algorithm for irrigation planning of rapeseed cultivation

引用

WATER SUPPLY 2023年第9期23卷 3856-3867页

作者： Dai, Yunzhong Chen, Kuan-yu Yibin Vocat & Tech Coll Intelligent Mfg Inst Yibin 644003 Sichuan Peoples R China Sichuan Dawn Precis Technol Co Ltd Meishan 620460 Sichuan Peoples R China Univ Elect Sci & Technol China Sch Aeronaut & Astronaut Chengdu 611731 Sichuan Peoples R China Yulin Normal Univ Sch Polit Sci & Law Yulin 537000 Guangxi Peoples R China

Sustainable planning of water allocation in the agricultural sector requires attention to soil, plant, climate and their limitations. This study was conducted in order to develop a real-time framework for simulating soil-water balance in the root zone, crop growth curve and irrigation planning of rapeseed cultivation in Henan Province, China during a cropping season from March to October 2022. Simulation of production functions with field information calibration at daily time step was developed to accurately estimate the simulation of crop growth and soil water balance. Particle swarm optimization (PSO) algorithm is incorporated as an efficient tool to evaluate the water productivity as objective function in a self-organizing framework. Choosing the appropriate planting date for rapeseed cultivation at the beginning of the growing season was evaluated to increase the use of precipitation for canopy cover growth and thus reduce irrigation water consumption. The results showed that the proposed model increased water productivity by 23% as the objective function, and evaporation from the soil surface decreased by 16%. The maximum difference between the irrigation depth in the optimal and existing strategies was 41 mm in the germination stages until the seed-filling stage, which caused a decrease in final biomass and plant transpiration.

关键词： canopy cover objective functions particle swarm optimization water use efficiency

来源：评论

学校读者我要写书评

暂无评论

Control Stochastic Selection-Based Biomedical Text Summarization Using Sim-TLBO

引用

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2024年第3期49卷 3593-3607页

作者： Gupta, Supriya Sharaff, Aakanksha Nagwani, Naresh Kumar Natl Inst Technol Raipur Dept Comp Sci & Engn Raipur India

The biomedical field specialists often face difficulties in summarization of available online literature. The biomedical archives like PubMed contain large set of lengthy documents, which needs to be shortened for further analysis of relevant data. In this work, we have introduced Similarity-specific Teaching and Learning-based optimization (Sim-TLBO) framework, which is combined with controlled stochastic selection of most relevant sentences for effective summarization. This method of utilizing metaheuristic teaching-learning approach along with multiple objective functions analysis provided an agile and robust solution. The output summary from the proposed solution is evaluated and compared based on ROUGE performance and various objective parameters including cohesion, non-redundancy, coverage, and readability. The hybrid text similarity (HTS) based on BERT similarity technique resulted in optimum ROUGE-1 values of 0.82 and 0.79 at 50% and 30% compression rates, respectively. The results from the presented framework when compared to other benchmark and baseline summarization models demonstrated significant performance improvement.

关键词： Sim-TLBO Control stochastic selection HTS BERT Biomedical text summarization objective functions

来源：评论

学校读者我要写书评

暂无评论

The linguistic dead zone of value-aligned agency, natural and artificial

引用

PHILOSOPHICAL STUDIES 2024年 1-23页

作者： Lacroix, Travis Univ Durham Dept Philosophy Durham England

The value alignment problem for artificial intelligence (AI) asks how we can ensure that the "values"-i.e., objective functions-of artificial systems are aligned with the values of humanity. In this paper, I argue that linguistic communication is a necessary condition for robust value alignment. I discuss the consequences that the truth of this claim would have for research programmes that attempt to ensure value alignment for AI systems-or, more loftily, those programmes that seek to design robustly beneficial or ethical artificial agents.

关键词： Artificial intelligence AI The value alignment problem Principal-agent problems Machine learning objective functions Normative theory Language Linguistic communication Communication systems Information transfer Coordination Values Preferences objectives Incentives

来源：评论

学校读者我要写书评

暂无评论

How Is the objective Function of the Feature Selection Problem Formulated? 7th

How Is the Objective Function of the Feature Selection Probl...

引用

7th International Conference on Optimization and Learning

作者： Cisternas-Caneo, Felipe Barrera-Garcia, Jose Crawford, Broderick Soto, Ricardo Gomez Sanchez, Mariam Manuel Gomez-Pulido, Jose Garces-Jimenez, Alberto Pontificia Univ Catolica Valparaiso Valparaiso Chile Univ Tecn Federico Santa Maria Valparaiso Chile Univ Alcala Dept Ciencias Computac Madrid Spain

ISBN: (纸本)9783031779404;9783031779411

This paper comprehensively analyzes objective functions used in feature selection, a critical aspect of machine learning. We conducted a systematic literature review, categorizing objective functions into single-objective and multi-objective, with further classification into pure and weighted multi-objective functions. Our study spans research from 2019 to 2023, analyzing 161 articles. We found that weighted multi-objective functions are most prevalent, highlighting their efficacy in balancing model performance and complexity. This work offers a detailed classification of these functions, contributing to a deeper understanding of their role and effectiveness in feature selection challenges. Our findings illuminate trends and preferences in objective function usage, providing valuable insights for researchers and practitioners in machine learning.

关键词： Future selection objective functions Literature Review Multi-objective Optimization

来源：评论

学校读者我要写书评

暂无评论

Meta-heuristic algorithms: an appropriate approach in crack detection

引用

INNOVATIVE INFRASTRUCTURE SOLUTIONS 2024年第7期9卷 1-22页

作者： Ghannadiasl, Amin Ghaemifard, Saeedeh Univ Mohaghegh Ardabili Dept Civil Engn Ardebil *** Iran

A structural fault is a significant factor that represents a safety hazard in the proper functioning of the structure. Thus, the crack should be detected and remade before the diffusion and demolition of a structure. One of the famous techniques to identification damage and fault, are the optimization-based methods. In these methods, by an optimization algorithm within an iterative process an objective subordinates minimized. For damage recognizing methodology, these optimization algorithms have a remarkable efficient so that a broad type of them are utilized in identification problems. In other words, these algorithms can find acceptable solutions to optimize complex problems. Therefore, these heuristic algorithms use in various optimization problems like structures. The recognition of structural degradation has attracted the attention of many researchers in the past decades. Hence, the progress of crack detection using meta-heuristic algorithms and artificial intelligence is investigated in all types of structures, such as beams in this paper. This paper is purposed to help researchers in acquaintance performance of algorithms for structural damage detection and to develop more reliable and applicable methods for civil engineering structures in the future.

关键词： Meta-heuristic algorithms Inverse problems Artificial intelligence objective functions Optimization Damage detection Crack

来源：评论

学校读者我要写书评

暂无评论

Trajectory optimisation in electrical discharge machining of three-dimensional curved and twisted channels

引用

Chinese Journal of Aeronautics 2022年第4期35卷 473-484页

作者： Jianshe ZHAO Yicong QIU Jian YUAN Chao LIU College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016China Laboratory of Integrated Electrical Processing Nanjing HANGPU Machinery Technology Company LimitedNanjing 210000China Military Representative Bureau of the Air Force Equipment Department in Shanghai and Military Representative Office in Zhuzhou Region Zhuzhou 412002China AECC South Industry Company Limited Zhuzhou 412002China

Numerical control electrical discharge machining(NC EDM) is one of the most widely used machining technologies for manufacturing a closed blisk flow path, particularly for three-dimensional(3D) curved and twisted flow channels. In this process, tool electrode design and machining trajectory planning are the key factors affecting machining accessibility and efficiency. Herein, to reduce the difficulty in designing the electrode and its motion path in the closed curved and twisted channels, a heuristic search hybrid optimisation strategy based on channel grids is adopted to realise the initial electrode trajectory design search and optimised size reduction. By transferring the trajectory optimisation constraints from the complex free-form surface to numbered grids, the search is found to be more orderly and accurate. The two trajectory indicators, namely argument angle and minimum distance, are analysed separately for the optimised results of the adaptive learning particle swarm optimisation algorithm, demonstrating that they can meet the actual processing *** results of NC EDM indicate that the motion path generated by this design method can meet the machining requirements of 3D curved and twisted flow channels.

关键词： Blisk Electrical discharge machining(EDM) Electrode objective functions Trajectory generation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：