A novel recurrent neural network forecasting model for power intelligence center

In order to accurately forecast the load of power system and enhance the stability of the power network, a novel unascertained mathematics based recurrent neural network (UMRNN) for power intelligence center (PIC) was created through three steps. First, by combining with the general project uncertain element transmission theory (GPUET), the basic definitions of stochastic, fuzzy, and grey uncertain elements were given based on the principal types of uncertain information. Second, a power dynamic alliance including four sectors: generation sector, transmission sector, distribution sector and customers was established. The key factors were amended according to the four transmission topologies of uncertain elements, thus the new factors entered the power intelligence center as the input elements. Finally, in the intelligence handing background of PIC, by performing uncertain and recursive process to the input values of network, and combining unascertained mathematics, the novel load forecasting model was built. Three different approaches were put forward to forecast an eastern regional power grid load in China. The root mean square error (ERMS) demonstrates that the forecasting accuracy of the proposed model UMRNN is 3% higher than that of BP neural network (BPNN), and 5% higher than that of autoregressive integrated moving average (ARIMA). Besides, an example also shows that the average relative error of the first quarter of 2008 forecasted by UMRNN is only 2.59%, which has high precision.

Multi-objective coordination optimal model for new power intelligence center based on hybrid algorithm

In order to resolve the coordination and optimization of the power network planning effectively, on the basis of introducing the concept of power intelligence center (PIC), the key factor power flow, line investment and load that impact generation sector, transmission sector and dispatching center in PIC were analyzed and a multi-objective coordination optimal model for new power intelligence center (NPIC) was established. To ensure the reliability and coordination of power grid and reduce investment cost, two aspects were optimized. The evolutionary algorithm was introduced to solve optimal power flow problem and the fitness function was improved to ensure the minimum cost of power generation. The gray particle swarm optimization (GPSO) algorithm was used to forecast load accurately, which can ensure the network with high reliability. On this basis, the multi-objective coordination optimal model which was more practical and in line with the need of the electricity market was proposed, then the coordination model was effectively solved through the improved particle swarm optimization algorithm, and the corresponding algorithm was obtained. The optimization of IEEE30 node system shows that the evolutionary algorithm can effectively solve the problem of optimal power flow. The average load forecasting of GPSO is 26.97 MW, which has an error of 0.34 MW compared with the actual load. The algorithm has higher forecasting accuracy. The multi-objective coordination optimal model for NPIC can effectively process the coordination and optimization problem of power network.

HIPPO artificial intelligence:Correlating automated radiographic femoroacetabular measurements with patient-reported outcomes in developmental hip dysplasia

BACKGROUND Hip dysplasia(HD)is characterized by insufficient acetabular coverage of the femoral head,leading to a predisposition for osteoarthritis.While radiographic measurements such as the lateral center edge angle(LCEA)and Tönnis angle are essential in evaluating HD severity,patient-reported outcome measures(PROMs)offer insights into the subjective health impact on patients.AIM To investigate the correlations between machine-learning automated and manual radiographic measurements of HD and PROMs with the hypothesis that artificial intelligence(AI)-generated HD measurements indicating less severe dysplasia correlate with better PROMs.METHODS Retrospective study evaluating 256 hips from 130 HD patients from a hip preservation clinic database.Manual and AI-derived radiographic measurements were collected and PROMs such as the Harris hip score(HHS),international hip outcome tool(iHOT-12),short form(SF)12(SF-12),and Visual Analogue Scale of the European Quality of Life Group survey were correlated using Spearman's rank-order correlation.RESULTS The median patient age was 28.6 years(range 15.7-62.3 years)with 82.3%of patients being women and 17.7%being men.The median interpretation time for manual readers and AI ranged between 4-12 minutes per patient and 31 seconds,respectively.Manual measurements exhibited weak correlations with HHS,including LCEA(r=0.18)and Tönnis angle(r=-0.24).AI-derived metrics showed similar weak correlations,with the most significant being Caput-Collum-Diaphyseal(CCD)with iHOT-12 at r=-0.25(P=0.042)and CCD with SF-12 at r=0.25(P=0.048).Other measured correlations were not significant(P>0.05).CONCLUSION This study suggests AI can aid in HD assessment,but weak PROM correlations highlight their continued importance in predicting subjective health and outcomes,complementing AI-derived measurements in HD management.

A Survey of Human-centered Intelligent Robots:Issues and Challenges

Intelligent techniques foster the dissemination of new discoveries and novel technologies that advance the ability of robots to assist and support humans. The human-centered intelligent robot has become an important research field that spans all of the robot capabilities including navigation, intelligent control, pattern recognition and human-robot interaction. This paper focuses on the recent achievements and presents a survey of existing works on human-centered robots. Furthermore, we provide a comprehensive survey of the recent development of the human-centered intelligent robot and discuss the issues and challenges in the field.

China National Research Center of Intelligent Equipment for Agriculture

China National Research Center of Intelligent Equipment for Agriculture （NRCIEA） was established in 2009 on the basis of Beijing Research Center of Intelligent Equipment for Agriculture. According to the development trend of world Intelligent Equipment for Agriculture （lEA） and China＇s needs of modern agriculture, NRCIEA is engaged in solving the key, fundamental and common technical problems in lEA.

Development of a Simulation-Based Intelligent Decision Support System for the Adaptive Real-Time Control of Flexible Manufacturing Systems

This paper describes a simulation-based intelligent decision support system (IDSS) for real time control of a flexible manufacturing system (FMS) with machine and tool flexibility. The manufacturing processes involved in FMS are complicated since each operation may be done by several machining centers. The system design approach is built around the theory of dynamic supervisory control based on a rule-based expert system. The paper considers flexibility in operation assignment and scheduling of multi-purpose machining centers which have different tools with their own efficiency. The architecture of the proposed controller consists of a simulator module coordinated with an IDSS via a real time event handler for implementing inter-process synchronization. The controller’s performance is validated by benchmark test problem.

高校图书馆未来学习中心建设路径及思考

未来学习中心致力于构建以读者为中心、以研究为导向、以兴趣为动力的全新学习生态。高校图书馆未来学习中心建设要突出空间再造和AI技术融合,通过改变传统空间布局来挖掘自身空间的价值和优势,把智慧图书馆空间融入学校整体发展中,打造团队式、协作式、主题式的图书馆智慧学习空间,以助力提升高校整体教育教学质量。文章从空间再造和智慧图书馆两个方面讨论构建高校图书馆未来学习中心的基本路径,介绍了西安建筑科技大学图书馆围绕未来学习中心建设所采取的措施,提出了建设高校图书馆未来学习中心的建议。

高校图书馆未来学习中心建设路径探寻

信息技术的飞速发展引发了教育理念、教学模式的变革,促使用户学习方式发生结构性改变,深刻影响到图书馆的转型发展。未来学习中心建设是高校图书馆高度关注高等教育变革需求、发挥新时代服务育人职能的新途径。文章借助文献调查、网络调查等方法,扫描、分析了高校图书馆主导建设未来学习中心面临的机遇与挑战,并结合安徽大学未来学习中心的初期实践,探寻未来路径的建设策略。

生成式人工智能背景下企业知识管理系统的构建及发展

通过文献调查法和类比分析法,以企业知识创新产出为核心目标,将知识管理的发展归纳为3个不同的时代,并鉴于仿生学、工程学、管理学三者的交叉对比,构建智能生成时代知识管理系统的基本框架,并将人工智能(AI)技术、智能中心、知识资产作为智能知识管理的三大要素,最后提出元宇宙虚拟世界和现实世界相结合的开放型知识管理构想理念模型。研究(1)明晰了生成式AI未来将渗透到各个组织层面的发展趋势;(2)结合主客观因素提出了生成式AI企业知识管理系统的基本框架及运作机理,为有效解决组织知识创新产出的内涵及运转提供了新的思路;(3)理论上建立了以智能中心为核心驱动力的知识创新管理理论系统,为生成式AI产业的智能发展提供了一定的理论支撑。

Tool wear condition monitoring method of five-axis machining center based on PSO-CNN

The effective monitoring of tool wear status in the milling process of a five-axis machining center is important for improving product quality and efficiency,so this paper proposes a CNN convolutional neural network model based on the optimization of PSO algorithm to monitor the tool wear status.Firstly,the cutting vibration signals and spindle current signals during the milling process of the five-axis machining center are collected using sensor technology,and the features related to the tool wear status are extracted in the time domain,frequency domain and time-frequency domain to form a feature sample matrix;secondly,the tool wear values corresponding to the above features are measured using an electron microscope and classified into three types:slight wear,normal wear and sharp wear to construct a target Finally,the tool wear sample data set is constructed by using multi-source information fusion technology and input to PSO-CNN model to complete the prediction of tool wear status.The results show that the proposed method can effectively predict the tool wear state with an accuracy of 98.27%;and compared with BP model,CNN model and SVM model,the accuracy indexes are improved by 9.48%,3.44%and 1.72%respectively,which indicates that the PSO-CNN model proposed in this paper has obvious advantages in the field of tool wear state identification.

基于“一中心四平台”的公立医院后勤运营管理实践研究

目的探讨基于“一中心四平台”的医院后勤运营管理模式成效。方法以医院智慧管理分级评估标准为依据,依托大数据、物联网、互联网+、人工智能等技术运用,打造后勤智慧运维管理中心以及设备管控信息化平台、安全防范信息化平台、能耗监测信息化平台、运营管理信息化平台的“一中心四平台”运营管理模式。结果经过样本医院的管理实践证明:基于“智慧联动”的设备故障处置能力得到显著提升,2022年故障报警次数同比2021年下降28.63%,其中高级、普通报警次数同比2021年分别下降69.53%、33.15%;基于“一站式”的后勤服务保障能力得到显著提升,2022年同比2021年维修次数下降2.92%,维修质量有所提高,反复维修频次降低;基于“数据挖掘”的能耗管控能力得到显著提升,2022年万元收入能耗支出同比2021年下降8.71%。结论“一中心四平台”可以显著提高后勤运维管理水平。

基于MR技术的智能配送中心虚拟仿真实训平台教学实践研究

随着信息技术的发展,传统物流管理正在演进到与数字化智能技术深度融合的智能物流新阶段,将混合现实技术(MR)应用于虚拟仿真实训平台建设,解决物流管理专业实训教学三高三难问题,激发学生获取专业知识和技能的兴趣,本研究通过在《配送中心运营管理》课程应用MR技术搭建虚拟仿真实训平台,进行数字化教学改革实践为例,对智慧供应链专业群的实训教学条件建设、教学过程设计、教学资源开发、教学效率的提升进行了有益的探索,希望为高职实训教学提供有效的教学参考。

6I未来学习中心:高校图书馆数智赋能教学科研服务新探

2021年底,教育部提出鼓励一批高校依托图书馆试点建设一批“未来学习中心”,但至今未出台建设方案。高校图书馆积极性很高,却并不十分清楚未来学习中心的建设理念、目标定位、建设方案、落地举措与服务内容。国内外可供借鉴的、符合高校图书馆定位的现成案例极少,亟待理论指导。本文综合考察全球具有影响力的教育与科研数智转型现状与趋势报告、我国多重国家战略需求、QS世界大学排名前150所高校的学习中心建设情况以及师生需求等内容,提出通过建设6I未来学习中心、使高校图书馆数智赋能教学科研服务的六个方面举措,即打造融合空间、营造智能氛围、提供交互支持、实现万物智联、培育创新能力、培养国际视野,因6个英译标题动词后第一个英文实词首字母均为I,故统称为“6I”。表1。参考文献27。

基于深度学习的智能问答型智慧校园平台设计

目前智慧校园数据中心存在数据质量较差、数据应用困难、数据分析收益较小等问题,设计基于深度学习技术的智能问答式数据中心,可以对智慧校园复杂数据的高效应用及梳理提供平台化的支撑。相对于传统的推荐技术与数据可视化技术,问答式数据中心能够直接给出数据分析人员关心的问题答案,有效降低数据分析成本。

3E教学模式在《人工智能与大数据导论》课程中的应用

针对目前《人工智能与大数据导论》课程在高职院校教学中的突出问题,提出优化教学方法的思路,并探索以学生为中心的3E教学模式贯穿线上线下教学的新方法,同时结合过程化考核方式,有助于最大程度地调动学生的积极性,更好地培养学生的实践能力和创新能力。

数智时代高校图书馆电子资源服务模式重构

为解决传统电子资源服务无法提供深层次、个性化、智能化的学科知识服务等问题,以数智技术赋能,为高校图书馆电子资源服务数字化转型提供新的视角。通过调研分析高校图书馆现行服务方式的优缺点和技术馆员的需求,充分利用数智技术,提出由智能网关、智能数据中台和智慧服务层三大模块组成的数智融合电子资源智慧服务架构,以大数据、智能技术作为电子资源访问服务需求和技术应用的桥梁,基于智能网关、智能数据中台架构为读者提供智能推荐服务,重构电子资源智慧服务模式,实现读者无感知访问、多模态电子资源分类和个性化阅读推荐,推动高校图书馆电子资源服务向以“资源组织和流程重组”为核心的数字化转型。

基于智慧物流理念的皮革企业“双中台”物流系统构建研究

针对大中型皮革企业生产过程中物流管理业务量大、数据类型丰富及时效性要求较高等问题,借鉴“互联网+”与智慧物流等新型理念构建一种针对大中型皮革企业的智慧物流体系。该体系由业务中台和数据中台搭建而成,“双中台”的设计方式能够很好地解决皮革企业物流业务响应慢、重复操作多及“数据孤岛”等问题,有效提升企业物流系统工作效率。

未来学习中心理念下图书馆教学支持研究

在多元智能技术驱动下,图书馆需抓住未来学习中心的发展契机,发挥海量资源优势,重塑以学习者为中心的教学支持环境,实现用户、空间和知识三元互联的发展愿景。文章回溯未来学习中心文献理论研究,分析图书馆未来教学支持研究的必要性。在智慧学习的理念下探索未来教学支持空间建设和服务平台架构。通过融合传统教学、发展特色学科、培养创新及应用能力,打造互动、开放的新型智慧教学空间,搭建智能技术立体互联、5G课程资源体系为基础、智慧馆员深度嵌入的服务平台架构,最后根据教学过程,开发定制式资源匹配、课程跟踪、跨学科交流及交互体验的未来教学支持场景。

基于UDI技术的单件器械追溯系统建设与应用探讨

为提高单件器械在回收、清洗、核包、灭菌及使用等环节的追溯精准度,提高贵重器械的利用率和成本管控水平,医院在消毒供应中心物品追溯系统信息化平台上,开发了“基于UDI技术的消毒供应中心单件器械追溯系统”。通过在单件器械上刻印UDI,在回收、器械组配两个环节扫描UDI码,记录单件器械的使用次数、单包清洗灭菌次数和单包使用明细,有效减少不必要的浪费,降低清洗消毒成本和器械采购开支,为手术质量管理提供支持。

数智化时代自动化专业实验教学体系改革探索

基于互联网、大数据、人工智能等新一代信息技术相互融合与集成创新,推动社会迈向人机协同、跨界融合、共创共享的数智化时代。在此背景下,深刻分析了自动化专业人才培养面临的问题与挑战,提出了“一中心五融合”的实验教学理念,优化教学模式,形成了“五类型、五模块、三平台”的实验教学体系。通过重构实验教学体系,为人才培养提供了有力保障,将更好地服务于自动化专业实验基础建设,也为相关专业课程改革提供了一定的借鉴。