检索结果-南通市图书馆

Balancing Exploration–Exploitation of Multi-verse Optimizer for Parameter Extraction on Photovoltaic Models

Journal of Bionic Engineering 2024年第2期21卷 1022-1054页

作者： Yan Han Weibin Chen Ali Asghar Heidari Huiling Chen Xin Zhang College of Computer Science and Artificial Intelligence Wenzhou UniversityWenzhou325035China School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran School of Biomedical Engineering National Engineering Research Center of Ophthalmology and OptometryEye HospitalWenzhou Medical UniversityWenzhou325027China key Lab of Biohealth Materials and Chemistry of Wenzhou Wenzhou UniversityWenzhouChina key laboratory of intelligent informatics for safety&emergency of zhejiang province Wenzhou UniversityWenzhouChina

Extracting photovoltaic(PV)model parameters based on the measured voltage and current information is crucial in the simulation and management of PV systems.To accurately and reliably extract the unknown parameters of different PV models,this paper proposes an improved multi-verse optimizer that integrates an iterative chaos map and the Nelder–Mead simplex method,INMVO.Quantitative experiments verified that the proposed INMVO fueled by both mechanisms has more affluent populations and a more reasonable balance between exploration and exploitation.Further,to verify the feasibility and competitiveness of the proposal,this paper employed INMVO to extract the unknown parameters on single-diode,double-diode,three-diode,and PV module four well-known PV models,and the high-performance techniques are selected for comparison.In addition,the Wilcoxon signed-rank and Friedman tests were employed to test the experimental results statistically.Various evaluation metrics,such as root means square error,relative error,absolute error,and statistical test,demonstrate that the proposed INMVO works effectively and accurately to extract the unknown parameters on different PV models compared to other techniques.In addition,the capability of INMVO to stably and accurately extract unknown parameters was also verified on three commercial PV modules under different irradiance and temperatures.In conclusion,the proposal in this paper can be implemented as an advanced and reliable tool for extracting the unknown parameters of different PV models.Note that the source code of INMVO is available at https://***/woniuzuioupao/INMVO.

关键词： Photovoltaic models Multi-verse optimizer Nelder-Mead simplex Iterative chaos map

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Gaussian Backbone-Based Spherical Evolutionary Algorithm with Cross-search for Engineering Problems

引用

Journal of Bionic Engineering 2024年第2期21卷 1055-1091页

作者： Yupeng Li Dong Zhao Ali Asghar Heidari Shuihua Wang Huiling Chen Yudong Zhang College of Computer Science and Technology Changchun Normal UniversityChangchun130032JilinChina School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehranIran School of Computing and Mathematical Sciences University of LeicesterLeicesterLE17RHUK Department of Biological Sciences Xi’an Jiaotong-Liverpool UniversitySuzhou215123JiangsuChina key laboratory of intelligent informatics for safety and emergency of zhejiang province Wenzhou UniversityWenzhou325035China School of Computer Science and Engineering Southeast UniversityNanjing210096China

In recent years,with the increasing demand for social production,engineering design problems have gradually become more and more complex.Many novel and well-performing meta-heuristic algorithms have been studied and developed to cope with this problem.Among them,the Spherical Evolutionary Algorithm(SE)is one of the classical representative methods that proposed in recent years with admirable optimization performance.However,it tends to stagnate prematurely to local optima in solving some specific problems.Therefore,this paper proposes an SE variant integrating the Cross-search Mutation(CSM)and Gaussian Backbone Strategy(GBS),called CGSE.In this study,the CSM can enhance its social learning ability,which strengthens the utilization rate of SE on effective information;the GBS cooperates with the original rules of SE to further improve the convergence effect of SE.To objectively demonstrate the core advantages of CGSE,this paper designs a series of global optimization experiments based on IEEE CEC2017,and CGSE is used to solve six engineering design problems with constraints.The final experimental results fully showcase that,compared with the existing well-known methods,CGSE has a very significant competitive advantage in global tasks and has certain practical value in real applications.Therefore,the proposed CGSE is a promising and first-rate algorithm with good potential strength in the field of engineering design.

关键词： Meta-heuristic algorithms Engineering optimization Spherical evolution algorithm Global optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Boosting Whale Optimizer with Quasi-Oppositional Learning and Gaussian Barebone for Feature Selection and COVID-19 Image Segmentation

引用

Journal of Bionic Engineering 2023年第2期20卷 797-818页

作者： Jie Xing Hanli Zhao Huiling Chen Ruoxi Deng Lei Xiao key laboratory of intelligent informatics for safety&emergency of zhejiang province Wenzhou UniversityWenzhou325035China

Whale optimization algorithm(WOA)tends to fall into the local optimum and fails to converge quickly in solving complex problems.To address the shortcomings,an improved WOA(QGBWOA)is proposed in this work.First,quasi-opposition-based learning is introduced to enhance the ability of WOA to search for optimal solutions.Second,a Gaussian barebone mechanism is embedded to promote diversity and expand the scope of the solution space in WOA.To verify the advantages of QGBWOA,comparison experiments between QGBWOA and its comparison peers were carried out on CEC 2014 with dimensions 10,30,50,and 100 and on CEC 2020 test with dimension 30.Furthermore,the performance results were tested using Wilcoxon signed-rank(WS),Friedman test,and post hoc statistical tests for statistical analysis.Convergence accuracy and speed are remarkably improved,as shown by experimental results.Finally,feature selection and multi-threshold image segmentation applications are demonstrated to validate the ability of QGBWOA to solve complex real-world problems.QGBWOA proves its superiority over compared algorithms in feature selection and multi-threshold image segmentation by performing several evaluation metrics.

关键词： Whale optimization algorithm Quasi-opposition-based learning Gaussian barebone Image segmentation Feature selection Bionic algorithm

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

BEDiff: denoising diffusion probabilistic models for building extraction

引用

Optoelectronics Letters 2024年

作者： LEI Yanjing WANG Yuan CHAN Sixian HU Jie ZHOU Xiaolong ZHANG Hongkai College of Computer Science and Technology zhejiang University of Technology Hubei key laboratory of intelligent Vision Based Monitoring for Hydroelectric Engineering The College of Computer and Information China Three Gorges University key laboratory of intelligent informatics for safety & emergency of zhejiang province Wenzhou University The College of Electrical and Information Engineering Quzhou University The School of Electronic and Information Engineering Anhui Jianzhu University

Accurately identifying building distribution from remote sensing images with complex background information is challenging. The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds. Building on this concept， we propose a novel framework， BEDiff， which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion. Our approach begins with the design of Booster Guidance， a mechanism that extracts structural and semantic features from remote sensing images to serve as priors， thereby providing targeted guidance for the diffusion process. Additionally， we introduce a Cross-Feature Fusion Module (CFM) that bridges the semantic gap between different types of features， facilitating the integration of the attributes extracted by Booster Guidance into the diffusion process more effectively. Our proposed BEDiff marks the first application of diffusion models to the task of building extraction. Empirical evidence from extensive experiments on the Beijing Building Dataset demonstrates the superior performance of BEDiff， affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

A novel neuroprotective method against ischemic stroke by accelerating the drainage of brain interstitial fluid

引用

Science China Life Sciences 2024年

作者： Jingge Lian Liu Yang Hanbo Tan Shaoyi Su Leonor Serrano Lopes Fangxiao Cheng Junhao Yan Yu Fu Wanyi Fu Zhaoheng Xie Jianfei Sun Jicong Zhang Zhiqian Tong Yajuan Gao Hongbin Han key laboratory of Alzheimer's Disease of zhejiang province Institute of Aging School of Mental Health Wenzhou Medical University NMPA key laboratory for Evaluation of Medical Imaging Equipment and Technique Department of Radiology Peking University Third Hospital Beijing key laboratory of Magnetic Resonance Imaging Technology Institute of Medical Technology Peking University Health Science Center Department of informatics Technical University of Munich Department of Anatomy and Histology School of Basic Medical Sciences Peking University Department of Neurology Peking University Third Hospital Department of Electronic Engineering Tsinghua University State key laboratory of Bioelectronics School of Biological Science and Medical Engineering Southeast University School of Biological Science and Medical Engineering Beihang University

Ischemic stroke is a leading cause of death and disability worldwide. Inflammatory response after stroke determines the outcome of ischemic injury. A recent study has reported an efficient method, epidural arterial implantation(EAI), for accelerating interstitial fluid(ISF)drainage, which provides a promising strategy to clear pro-inflammatory cytokines in the brain extracellular space(ECS). In this study, the method of EAI was modified(m-EAI) to control its function of accelerating the ISF drainage at different time points following ischemic attack. The neuroprotective effect of m-EAI on ischemic stroke was evaluated with the transient middle cerebral artery occlusion(tMCAO)rat model. The results demonstrated the accumulation of IL-1β, IL-6, and TNF-α was significantly decreased by activating m-EAI at 7 d before and immediately after ischemic attack in tMCAO rats, accompanied with decreased infarct volume and improved neurological function. This study consolidates the hypothesis of exacerbated ischemic damage by inflammatory response and provides a new perspective to treat encephalopathy via brain ECS. Further research is essential to investigate whether m-EAI combined with neuroprotective drugs could enhance the therapeutic effect on ischemic stroke.

关键词：

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Boosting Kernel Search Optimizer with Slime Mould Foraging Behavior for Combined Economic Emission Dispatch Problems

引用

Journal of Bionic Engineering 2023年第6期20卷 2863-2895页

作者： Ruyi Dong Lixun Sun Long Ma Ali Asghar Heidari Xinsen Zhou Huiling Chen College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin132000China School of Surveying and Geospatial Engineering College of EngineeringUniversity of TehranTehran***Iran key laboratory of intelligent informatics for safety&emergency of zhejiang province Wenzhou UniversityWenzhou325000China

Reducing pollutant emissions from electricity production in the power system positively impacts the control of greenhouse gas emissions.Boosting kernel search optimizer(BKSO)is introduced in this research to solve the combined economic emission dispatch(CEED)problem.Inspired by the foraging behavior in the slime mould algorithm(SMA),the kernel matrix of the kernel search optimizer(KSO)is intensified.The proposed BKSO is superior to the standard KSO in terms of exploitation ability,robustness,and convergence rate.The CEC2013 test function is used to assess the improved KSO's performance and compared to 11 well-known optimization algorithms.BKSO performs better in statistical results and convergence curves.At the same time,BKSO achieves better fuel costs and fewer pollution emissions by testing with four real CEED cases,and the Pareto solution obtained is also better than other MAs.Based on the experimental results,BKSO has better performance than other comparable MAs and can provide more economical,robust,and cleaner solutions to CEED problems.

关键词： Combined economic emission dispatch Kernel search optimization Slime mould algorithm Valve point effect Greenhouse gases

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Distributed Active Partial Label Learning

引用

intelligent Automation & Soft Computing 2023年第9期37卷 2627-2650页

作者： Zhen Xu Weibin Chen key laboratory of intelligent informatics for safety&emergency of zhejiang province Wenzhou UniversityWenzhou325006China College of Computer Science and Artificial Intelligence Engineering Wenzhou UniversityWenzhou325006China

Active learning(AL)trains a high-precision predictor model from small numbers of labeled data by iteratively annotating the most valuable data sample from an unlabeled data pool with a class label throughout the learning process.However,most current AL methods start with the premise that the labels queried at AL rounds must be free of ambiguity,which may be unrealistic in some real-world applications where only a set of candidate labels can be obtained for selected data.Besides,most of the existing AL algorithms only consider the case of centralized processing,which necessitates gathering together all the unlabeled data in one fusion center for selection.Considering that data are collected/stored at different nodes over a network in many real-world scenarios,distributed processing is chosen here.In this paper,the issue of distributed classification of partially labeled(PL)data obtained by a fully decentralized AL method is focused on,and a distributed active partial label learning(dAPLL)algorithm is proposed.Our proposed algorithm is composed of a fully decentralized sample selection strategy and a distributed partial label learning(PLL)algorithm.During the sample selection process,both the uncertainty and representativeness of the data are measured based on the global cluster centers obtained by a distributed clustering method,and the valuable samples are chosen in turn.Meanwhile,using the disambiguation-free strategy,a series of binary classification problems can be constructed,and the corresponding cost-sensitive classifiers can be cooperatively trained in a distributed manner.The experiment results conducted on several datasets demonstrate that the performance of the dAPLL algorithm is comparable to that of the corresponding centralized method and is superior to the existing active PLL(APLL)method in different parameter configurations.Besides,our proposed algorithm outperforms several current PLL methods using the random selection strategy,especially when only small amounts of data are selected to be assigned

关键词： Active learning partial label learning distributed processing disambiguation-free strategy

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Comprehensive Learning Strategy Enhanced Chaotic Whale Optimization for High-dimensional Feature Selection

引用

Journal of Bionic Engineering 2023年第6期20卷 2973-3007页

作者： Hanjie Ma Lei Xiao Zhongyi Hu Ali Asghar Heidari Myriam Hadjouni Hela Elmannai Huiling Chen key laboratory of intelligent informatics for safety&emergency of zhejiang province Wenzhou UniversityWenzhou325035China Department of Computer Sciences College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityP.O.Box 8442811671 RiyadhSaudi Arabia Department of Information Technology College of Computer and Information SciencePrincess Nourah Bint Abdulrahman UniversityP.O.Box 8442811671 RiyadhSaudi Arabia

Feature selection(FS)is an adequate data pre-processing method that reduces the dimensionality of datasets and is used in bioinformatics,finance,and medicine.Traditional FS approaches,however,frequently struggle to identify the most important characteristics when dealing with high-dimensional information.To alleviate the imbalance of explore search ability and exploit search ability of the Whale Optimization Algorithm(WOA),we propose an enhanced WOA,namely SCLWOA,that incorporates sine chaos and comprehensive learning(CL)strategies.Among them,the CL mechanism contributes to improving the ability to explore.At the same time,the sine chaos is used to enhance the exploitation capacity and help the optimizer to gain a better initial solution.The hybrid performance of SCLWOA was evaluated comprehensively on IEEE CEC2017 test functions,including its qualitative analysis and comparisons with other optimizers.The results demonstrate that SCLWOA is superior to other algorithms in accuracy and converges faster than others.Besides,the variant of Binary SCLWOA(BSCLWOA)and other binary optimizers obtained by the mapping function was evaluated on 12 UCI data sets.Subsequently,BSCLWOA has proven very competitive in classification precision and feature reduction.

关键词： Feature selection Whale Optimization Algorithm Binary optimizer Global optimization

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Enhanced Entropy-Based Resource Searching in Unstructured P2P Networks

引用

Chinese Journal of Electronics 2015年第2期24卷 229-235页

作者： GONG Weihua JIN Rong YANG Lianghuai HUANG Decai School of Computer Science and Technology Zhejiang University of Technology key laboratory of Visual Media intelligent Process Technology of zhejiang province School of informatics and Electronics Zhejiang Sci-Tech University

How to find desired resources efficiently and accurately is one fundamental challenge of any unstructured P2 P networks, which is mainly involved some difficulties in the P2 P overlay topology, data representation in peers and routing mechanism. In this paper, we address the issue of resilient routing in unstructured P2 P networks. An efficient algorithm called Query routing tree(QRT) based on maximum mutual information is proposed to improve the performance of resource searching, which has tightly associated the resource contents of peers with the logical links in P2 P network that makes the query messages forwarded more effectively in similar peers and can hit more target resources faster. Additionally, we present an optimized routing scheme with the query conditions taken into account, to obtain the optimal routing tree with the minimal information gain from the candidate tree set so as to adapt to different query types more flexibly. The simulation results show the proposed QRT can reduce the search cost more effectively and maintain higher targets hit rate than existing typical algorithms such as Flooding, k-RW and APS. Finally, our optimized scheme is also proved to conduct high searching performance with nicer self-adaptability and scalability in unstructured P2 P networks.

关键词： Peer-to-peer(P2P) Resource searching Entropy Query routing tree Information gain

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

Stratified Analysis of Survival Benefit for ABO-incompatible Deceased-donor Liver Transplantation:Multicenter Propensity Score-matched Study

引用

Journal of Clinical and Translational Hepatology 2023年第4期11卷 827-838页

作者： Mengfan Yang Xuyong Wei Abdul Rehman Khan Qiang Wei Rui Wang Binhua Pan Kun Wang Zhisheng Zhou Di Lu Beini Cen Shuijun Zhang Wenzhi Guo Shusen Zheng Yang Yang Xiao Xu Department of Organ Transplantation Qilu Hospital of Shandong UniversityJinanShandongChina key laboratory of Integrated Oncology and intelligent Medicine of zhejiang province HangzhouZhejiangChina Department of Hepatobiliary and Pancreatic Surgery Affiliated Hangzhou First People’s HospitalZhejiang University School of MedicineHangzhouZhejiangChina zhejiang University School of Medicine HangzhouZhejiangChina National Center for Healthcare Quality Management in Liver Transplant HangzhouZhejiangChina Department of Hepatobiliary and Pancreatic Surgery The First Affiliated Hospital of Zhengzhou UniversityHenanChina Department of Hepatobiliary and Pancreatic Surgery The First Affiliated HospitalZhejiang University School of MedicineHangzhouZhejiangChina Department of Hepatobiliary and Pancreatic Surgery Shulan(Hangzhou)HospitalHangzhouZhejiangChina Department of Hepatobiliary and Pancreatic Surgery The Third Affiliated Hospital of Sun Yat-Sen UniversityGuangzhouGuangdongChina

Background and Aims:Liver transplantation(LT)using ABO-incompatible(ABOi)grafts can extend the donor pool to a certain extent and hence reduce the waiting time for transplantation.However,concerns of the impending prognosis associated with this option,especially for patients with liver failure and higher model for end-stage liver disease(MELD)scores,who tend to be more fragile during the waiting period before LT.Methods:Recipients undergoing LT for acute-onchronic liver failure or acute liver failure were retrospectively enrolled at four institutions.Overall survival was compared and a Cox regression analysis was performed.Propensity score matching was performed for further comparison.Patients were stratified by MELD score and cold ischemia time(CIT)to determine the subgroups with survival benefits.Results:Two hundred ten recipients who underwent ABOi LT and 1,829 who underwent ABO compatible(ABOc)LT were enrolled.The 5-year overall survival rate was significantly inferior in the ABOi group compared with the ABOc group after matching(50.6%vs.75.7%,p0.05).Comparison of the survival rates revealed no statistically significant difference for patients with MELD scores≥40(p>0.05).For patients with MELD scores of 31-39,the overall survival rate was significantly inferior in the ABOi group compared with the ABOc group(pemergency cases.For recipients with MELD scores of 31-39,the ABOi LT prognosis was worse.However,those patients benefited from receiving ABOi grafts with a CIT of<8 h.

关键词： Liver transplantation ABO-incompatible Model for end-stage liver disease score Cold ischemia time Propensity score matching

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

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

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

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：