检索结果-内蒙古大学图书馆

您好，读者！请登录

内蒙古大学图书馆

首页
概况
党建
资源
服务
科研支持
- 论文收录引用证明
- 科技查新
知识产权
档案馆
帮助

咨询与建议

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

您的常用邮箱：*

您的手机号码：*

问题描述：

当前已输入0个字，您还可以输入200个字

全部搜索
期刊论文
图书
学位论文
标准
纸本馆藏
外文资源发现
数据库导航
超星发现

高级检索

时间限定

出版年份：

文献类型

图书期刊文献学位论文多媒体

馆藏选择

电子馆藏纸本馆藏

核心期刊

全部期刊 SCI 收录期刊 SSCI 收录期刊 EI 收录期刊 CSCD 收录期刊 CSSCI 收录期刊

语言

中文英文

文献类型

期刊文献图书学位论文标准纸本馆藏

帮助

文字说明：

T=题名（书名、题名），A=作者（责任者），K=主题词，P=出版物名称，PU=出版社名称，O=机构（作者单位、学位授予单位、专利申请人），L=中图分类号，C=学科分类号，U=全部字段，Y=年（出版发行年、学位年度、标准发布年）

检索规则说明：

AND代表“并且”；OR代表“或者”；NOT代表“不包含”；(注意必须大写,运算符两边需空一格)

检索范例：

范例一：(K=图书馆学 OR K=情报学) AND A=范并思 AND Y=1982-2016
范例二：P=计算机应用与软件 AND (U=C++ OR U=Basic) NOT K=Visual AND Y=2011-2016

分类表

所选分类

>> <<

限定检索结果

文献类型

126 篇 会议
35 篇 期刊文献
2 册 图书

馆藏范围

163 篇 电子文献
0 种 纸本馆藏

日期分布

学科分类号

85 篇 工学
- 61 篇 计算机科学与技术...
- 48 篇 软件工程
- 26 篇 控制科学与工程
- 25 篇 电气工程
- 19 篇 动力工程及工程热...
- 13 篇 信息与通信工程
- 10 篇 机械工程
- 6 篇 生物医学工程（可授...
- 6 篇 网络空间安全
- 5 篇 生物工程
- 4 篇 建筑学
- 3 篇 化学工程与技术
- 2 篇 光学工程
- 2 篇 电子科学与技术（可...
- 2 篇 土木工程
34 篇 管理学
- 24 篇 管理科学与工程(可...
- 14 篇 工商管理
- 14 篇 图书情报与档案管...
20 篇 理学
- 10 篇 数学
- 6 篇 生物学
- 5 篇 系统科学
- 3 篇 物理学
- 2 篇 化学
- 2 篇 统计学（可授理学、...
11 篇 医学
- 11 篇 基础医学(可授医学...
- 11 篇 临床医学
- 9 篇 公共卫生与预防医...
- 4 篇 药学(可授医学、理...
5 篇 经济学
- 5 篇 应用经济学
2 篇 法学
- 2 篇 社会学
1 篇 教育学
1 篇 农学

主题

12 篇 optimization
11 篇 demand response
9 篇 smart grids
8 篇 costs
7 篇 load management
7 篇 uncertainty
6 篇 distributed powe...
6 篇 forecasting
5 篇 scalability
5 篇 clustering
5 篇 microgrids
5 篇 recommender syst...
5 篇 electricity supp...
5 篇 buildings
5 篇 machine learning
5 篇 smart power grid...
5 篇 multi agent syst...
4 篇 energy consumpti...
4 篇 production
4 篇 renewable energy...

机构

9 篇 gecad - research...
8 篇 polytechnic of p...
7 篇 gecad - research...
7 篇 research group o...
5 篇 gecad - research...
4 篇 porto
4 篇 gecad - research...
4 篇 gecad - research...
3 篇 ipp - instituto ...
3 篇 lasi - intellige...
3 篇 gecad – research...
3 篇 algoritmi centre...
3 篇 gecad - research...
3 篇 gecad – research...
3 篇 bisite research ...
3 篇 gecad - research...
2 篇 research group o...
2 篇 gecad - research...
2 篇 medcids faculty ...
2 篇 research group o...

作者

63 篇 zita vale
35 篇 vale zita
34 篇 pedro faria
17 篇 marreiros goreti
16 篇 faria pedro
15 篇 tiago pinto
15 篇 gomes luis
14 篇 luis gomes
13 篇 fernando lezama
12 篇 ricardo faia
9 篇 isabel praça
8 篇 martins constant...
8 篇 bruno canizes
7 篇 ribeiro bruno
7 篇 joao soares
7 篇 conceição luís
7 篇 canizes bruno
7 篇 joão soares
7 篇 ramos carlos
6 篇 cátia silva

语言

150 篇 英文
7 篇 其他
6 篇 中文

检索条件"机构=GECAD - Knowledge Research Group on Intelligent Engineering and Computing for Advanced Innovation"

共 163 条记录，以下是131-140 订阅

全选清除本页清除全部题录导出标记到"检索档案"

详细简洁

排序：

Explainable Artificial Intelligence for Definition of Inputs in Neural Networks and K-nearest Neighbors Forecasting of Electricity Consumption

Explainable Artificial Intelligence for Definition of Inputs...

引用

IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： Daniel Ramos Pedro Faria Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto Portugal

Nowadays, data science and machine learning areas play a crucial role by performing predictions of energy with reliable historic of consumptions and other sensors data. This is crucial for decision makers to formulate an optimized plan to buy and sell energy ahead of time. According to many data scientists the decision criteria to select sensors to be added to the historic of consumptions consists on the sensors evidencing a higher correlation with the consumption variable. However, experts in the explainable artificial intelligence field study the positive and negative impact of the sensors to the prediction accuracy.. This paper analyzes the correlation of the sensors of a building to the consumption variable. Furthermore, explanations regarding the contribution of the consumption and sensors features to the forecasting performance are supported by an explainable artifial intelligence method named Local Interpretable Model Agnostic Explanation. The forecasted consumptions use two methods: Artificial Neural Network and K-nearest Neighbors.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Energy consumption forecasting based on Hybrid Neural Fuzzy Inference System

Energy consumption forecasting based on Hybrid Neural Fuzzy ...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Aria Jozi Tiago Pinto Isabel Praça Francisco Silva Brigida Teixeira Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto Portugal

Forecasting the electricity consumption is one of the most challenging tasks for energy domain stakeholders. Having reliable electricity consumption forecasts can help minimizing the cost of electricity and also enable a better control on the electricity tariff. This paper presents a study regarding the forecast of electricity consumption using a methodology based on Hybrid neural Fuzzy Inference System (HyFIS). The proposed approach considers two distinct strategies, namely one strategy using only the electricity consumption as the input of the method, and the second strategy uses a combination of the electricity consumption and the environmental temperature as the input. A case study considering the forecasting of the consumption of an office building using the proposed methodologies is also presented. Results show that the second strategy is able to achieve better results, hence concluding that HyFIS is an appropriate approach to incorporate different sources of information. In this way, the environmental temperature can help the HyFIS method to achieve a more reliable forecast of the electricity consumption.

关键词： Forecasting Buildings Training Fuzzy logic Databases Energy consumption Servers

来源：评论

学校读者我要写书评

暂无评论

Bilateral contract prices estimation using a Q-leaming based approach

Bilateral contract prices estimation using a Q-leaming based...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Jaime Rodríguez-Fernández Tiago Pinto Francisco Silva Isabel Praça Zita Vale Juan Manuel Corchado GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/IPP) Porto Portugal BISITE Research Centre University of Salamanca (USAL) Salamanca Spain

The electricity markets restructuring process encouraged the use of computational tools in order to allow the study of different market mechanisms and the relationships between the participating entities. Automated negotiation plays a crucial role in the decision support for energy transactions due to the constant need for players to engage in bilateral negotiations. This paper proposes a methodology to estimate bilateral contract prices, which is essential to support market players in their decisions, enabling adequate risk management of the negotiation process. The proposed approach uses an adaptation of the Q-Learning reinforcement learning algorithm to choose the best from a set of possible contract prices forecasts that are determined using several methods, such as artificial neural networks (ANN), support vector machines (SVM), among others. The learning process assesses the probability of success of each forecasting method, by comparing the expected negotiation price with the historic data contracts of competitor players. The negotiation scenario identified as the most probable scenario that the player will face during the negotiation process is the one that presents the higher expected utility value. This approach allows the supported player to be prepared for the negotiation scenario that is the most likely to represent a reliable approximation of the actual negotiation environment.

关键词： Contracts Electricity supply industry Tools Forecasting Adaptation models Learning (artificial intelligence) Estimation

来源：评论

学校读者我要写书评

暂无评论

Hybrid Particle Swarm Optimization of Electricity Market Participation Portfolio

Hybrid Particle Swarm Optimization of Electricity Market Par...

引用

IEEE Symposium Series on Computational Intelligence

作者： Ricardo Faia Tiago Pinto Zita Vale Juan Manuel Corchado GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/ IPP) Porto Portugal BISITE Research Centre University of Salamanca (USAL) Salamanca Spain

This paper proposes a novel hybrid particle swarm optimization methodology to solve the problem of optimal participation in multiple electricity markets. The decision time is usually very important when planning the participation in electricity markets. This environment is characterized by the time available to take action, since different electricity markets have specific rules, which requires participants to be able to adapt and plan their decisions in a short time. Using metaheuristic optimization, participants' time problems can be resolved, because these methods enable problems to be solved in a short time and with good results. This paper proposes a hybrid resolution method, which is based on the particle swarm optimization metaheuristic. An exact mathematical method, which solves a simplified, linearized, version of the problem, is used to generate the initial solution for the metaheuristic approach, with the objective of improving the quality of results without representing a significant increase of the execution time.

关键词： Artificial intelligence Electricity markets Hybrid resolution methods Portfolio optimization Metaheuristic optimization

来源：评论

学校读者我要写书评

暂无评论

Benders' decomposition applied to Energy Resource Management in smart distribution networks

Benders' decomposition applied to Energy Resource Management...

引用

Clemson University Power Systems Conference (PSC)

作者： J. Soares Bruno Canizes Z. Vale G. K. Venayagamoorthy GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto Portugal Real-Time Power and Intelligent Systems Lab. Clemson University Clemson SC USA

This paper proposes a Benders' decomposition approach for the large-scale Energy Resource Management (ERM). The problem considers large amount of Distributed Energy Resources (DER) including Electric Vehicles (EVs) with gridable capacity. The proposed model is designed for Virtual Power Players/Plants (VPPs) managing a smart distribution network with the aim to maximize profits considering the day-ahead time horizon. Previous literature has shown difficulties in solving similar problems using classical techniques in a centralized scheme, namely considering nonlinear network constrains. The proposed approach reduces computational burden of the original Mixed Integer Nonlinear Programming (MINLP) problem. The Benders' cuts are introduced for the ERM formulation in order to allow the communication between the slave and the master problem. Analysis of two large-scale instances have been carried out for smart distribution networks, namely a 33-bus and a real Portuguese 180-bus network assuming high penetration of DERs and EVs.

关键词： Energy resources Optimization Partial discharges Load flow Smart grids Processor scheduling Load management

来源：评论

学校读者我要写书评

暂无评论

Artificial Neural Network Based Efficient Maximum Power Point Tracking for Photovoltaic Systems

Artificial Neural Network Based Efficient Maximum Power Poin...

引用

International Conference on Environment and Electrical engineering (EEEIC)

作者： Ubaid ur Rehman Pedro Faria Luis Gomes Zita Vale Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto (ISEP/IPP) Porto Portugal

ISBN: (数字)9781665485371

ISBN: (纸本)9781665485388

In this paper, we propose a novel Artificial Neural Network (ANN) based Maximum Power Point Tracking (MPPT) technique to enhance the overall solar power generation and to regulate the voltage variations due to the varying solar irradiance levels by effectively controlling the duty cycle of the DC-DC Boost Converter. The proposed technique effectively regulates the voltage transients. Moreover, it also enhances the overall power production of the Photovoltaic (PV) plant. Simulation carried out in Matlab have proved effectiveness of the proposed ANN technique and to counter check its performance, these simulation results have been compared with the traditional perturb and observe maximum power point tracking technique. This results comparison proves that the proposed ANN-based MPPT technique exhibits optimal voltage regulation capability as compared to the traditional perturb and observe MPPT method, it provides better control under abrupt temperature and irradiance level variations.

关键词： Maximum power point trackers Photovoltaic systems Simulation Europe Artificial neural networks Production Temperature control

来源：评论

学校读者我要写书评

暂无评论

Virtual Power Plant Optimization Service-Benchmark of Solvers

Virtual Power Plant Optimization Service-Benchmark of Solver...

引用

Federated Conference on Computer Science and Information Systems (FedCSIS)

作者： Filipe Alves Rui Ribeiro Maria Petiz Ali Abbasi Pedro Carvalho Ricardo Faia Pedro Faria Zita Vaie Ricardo Rodrigues DTx—Digital Transformation CoLAB University of Minho Guimarães Portugal GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI-Intelligent Systems Associate Laboratory Polytechnic of Porto Porto Portugal

ISBN: (数字)9788396960160

ISBN: (纸本)9798350359718

This work provides a comprehensive analysis of the optimization of a Virtual Power Plant (VPP), that consider the presence of energy storage systems and controllable loads, through the benchmarking of various solvers. It delves into the development of a Mixed Integer Linear Programming (MILP) algorithm aiming at optimizing energy management and exchange within a VPP, that takes into account the operation of shift electric appliances and battery storage systems among different houses. The proposed model aims to minimize the overall electricity cost while ensuring that the energy demand of the system is met, the battery state of charge is maintained within safe operating limits, and the shift electrical appliance is scheduled. Furthermore, the experimental comparisons, the study evaluates the performance of commercial and open-source solvers in handling the complex dynamics of energy demand and supply. The findings highlight the importance of solver selection in enhancing the management, scalability, and reliability of VPP optimization strategies, offering insights into the optimal combination of programming interfaces and solvers for efficient VPP operation.

关键词： Energy consumption Scalability Virtual power plants Programming Batteries Mixed integer linear programming State of charge Reliability Optimization Load modeling

来源：评论

学校读者我要写书评

暂无评论

Evolutionary framework for multi-dimensional signaling method applied to energy dispatch problems in smart grids 19

Evolutionary framework for multi-dimensional signaling metho...

引用

19th International Conference on intelligent System Application to Power Systems, ISAP 2017

作者： Lezama, Fernando De Cote, Enrique Munoz Sucar, Luis Enrique Soares, Joao Vale, Zita Mexico PROWLER.io Ltd Cambridge United Kingdom GECAD-Res. Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Portugal

ISBN: (纸本)9781509040001

In the smart grid (SG) era, the energy resource management (ERM) in power systems is facing an increase in complexity, mainly due to the high penetration of distributed resources, such as renewable energy and electric vehicles (EVs). Therefore, advanced control techniques and sophisticated planning tools are required to take advantage of the benefits that SG technologies can provide. In this paper, we introduce a new approach called multi-dimensional signaling evolutionary algorithm (MDS-EA) to solve the large-scale ERM problem in SGs. The proposed method uses the general framework from evolutionary algorithms (EAs), combined with a previously proposed rule-based mechanism called multi-dimensional signaling (MDS). In this way, the proposed MDS-EA evolves a population of solutions by modifying variables of interest identified during the evaluation process. Results show that the proposed method can reduce the complexity of metaheuristics implementation while achieving competitive solutions compared with EAs and deterministic approaches in acceptable times. © 2017 IEEE.

关键词： Evolutionary algorithms

来源：评论

学校读者我要写书评

暂无评论

Electric Vehicles Uncertainty Forecasting

Electric Vehicles Uncertainty Forecasting

引用

Saudi Arabia Smart Grid Conference (SASG)

作者： Juliana Chavez Zahra Foroozandeh Sérgio Ramos João Soares Zita Vale GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto School of Engineering (ISEP) 4200-072 Porto Portugal Polytechnic of Porto School of Engineering (ISEP) 4200-072 Porto Portugal

The growing integration of electric vehicles has attracted a lot of interest. However, they are highly affected by EV charging uncertainties and are, therefore, difficult to forecast accurately. This paper presents an Artificial Neural Network (ANN) method ANN to forecast electric vehicle uncertainties. ANN was trained using historical data from a residential building, such as arrival time, departure time and initial SOC. Then, it was tested during 24 hours through different scenarios. For each one of the cases, the model’s accuracy was assessed by comparing historical data to forecast information. The associated errors were also calculated. The outcomes reveal that the suggested forecasting method is very effective in reducing EV forecasting errors and, as a result, is better at regulating EV uncertainty.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Brief Review on Optimal Network Planning Considering Energy Storage Systems and Uncertainty

A Brief Review on Optimal Network Planning Considering Energ...

引用

Future Energy Solutions (FES), International Conference on

作者： Fábio Castro João Soares Bruno Canizes Zita Vale GECAD -Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development LASI – Intelligent Systems Associate Laboratory Polytechnic of Porto R. Dr. António Bernardino de Almeida 431 Porto Portugal

The topic of optimal planning has always been relevant ever since modern-day electricity markets were established. With the increasing awareness for a stable future, environmentally renewable sources of electricity production have seen a major uprise in latest years. Along with its inherent benefits, this increase in penetration of renewable energy sources also causes some unforeseen issues, such as lower network flexibility since most renewable production is intermittent and unpredictable, and harder generation forecasting for the same reasons. Many authors have researched ways to mitigate these issues, and most point to utilizing energy storage systems. Energy storage and uncertainty are not necessarily new topics, but they are now more prominent than ever and a must in recent optimal planning models regarding electricity networks. This paper aims to highlight some contributions made by literature regarding the topic, focusing on models studying energy storage systems, models that consider uncertainty, and models that consider both.

关键词：

来源：评论

学校读者我要写书评

暂无评论

没有更多数据了...

全选清除本页清除全部题录导出标记到“检索档案”

共17页 << < 8 9 10 11 12 13 14 15 16 17 > >>

检索报告对象比较合并检索0

隐藏清空

合并搜索

回到顶部

执行限定条件

内容：

评分：

请选择保存的检索档案：

请选择收藏分类：

订阅名称：

通借通还

温馨提示：

图书名称：

借书校区：

取书校区：

手机号码：

邮箱地址：

一卡通帐号：

电话和邮箱必须正确填写，我们会与您联系确认。

联系人：

所在院系：

联系邮箱：

联系电话：

内蒙古自治区呼和浩特市赛罕区大学西街235号邮编: 010021

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：