Analysis and Modeling of the Central Air-Conditioning System in Intelligent Buildings

The central air conditioning system in an intelligent building (IB) was analyzed and modeled in order to perform the optimization scheduling strategy of the central air conditioning system. A set of models proposed and a type of periodically autoregressive model (PAR) based on the improved genetic algorithms (IGA) were used to perform the optimum energy saving scheduling. The example of the Liangmahe Plaza was taken to show the effectiveness of the methods.

Optimum Energy Management of the Central Air-Conditioning System in Intelligent Buildings

An optimum energy saving scheduling strategy of the central air conditioning system in an intelligent building (IB) was proposed. Based on the system analysis a set of models of the central air conditioning system was established. The periodically autoregressive models (PARM) based on genetic algorithms (GA) were used to predict the next day’s cold load. The improved genetic algorithms (IGA) with stochastic real number coding were used to finish the optimum energy saving scheduling of the system. The simulation results for the building of the Liangmahe Plaza show that the proposed strategy can save energy up to about 24 5%.

Improved Implementation and Evaluation of Wireless Sensor Networks in Intelligent Building

A complete study for the implementation of wireless sensor networks in the intelligent building is presented. We carry out some experiments to find out the factors affecting the network performance. Several vital parameters which are related to the link quality are measured before deploying the actual system. And then, we propose an optimized routing protocol based on the analysis of the test data. We evaluate the deployment strategies to ensure the excellent performance of the wireless sensor networks under the real working conditions. And the evaluation results show that the presented system could satisfy the requirements of the applications in the intelligent building.

Optimum Scheduling for the Chilled Water System of an Intelligent Building

The energy saving issue of chilled water system in an intelligent building is analyzed from the systematic point of view, and an optimum scheduling scheme which can save energy of the system facilities and satisfy the constraints of the real time cold loads and system running is also proposed. It can make the minimum cost of the system by optimizing the number of running chillers, running parameters and the distribution of real time loads of running chillers. The improved genetic algorithm is used in the optimum scheduling scheme. The computation results show that the building energy consumption can be decreased by about 10%.

Intelligent Building Load Scheduling Based on Multi-Objective Multi-Verse Algorithm

In the multi-objective of intelligent building load scheduling, aiming at the problem of how to select Pareto frontier scheme for multi-objective optimization algorithm, the current optimal scheme mechanism combined with multi-objective multi-verse algorithm is used to optimize the intelligent building load scheduling. The update mechanism is changed in updating the position of the universe, and the process of correction coding is omitted in the iterative process of the algorithm, which reduces the com-putational complexity. The feasibility and effectiveness of the proposed method are verified by the optimal scheduling experiments of residential loads.

Fault Diagnosis of an Intelligent Building Facility Using Bayesian Networks

There is great significance to diagnose the fault of an intelligent building facility for fault controlling, repairing, eliminating and preventing. As an example, this paper established a Bayesian networks model f or fault diagnosis of the refrigeration system of an intelligent building facility, gave the networks parameters, and analyzed the reasoning mechanism. Based on the model, some data was analyzed and diagnosed by adopting Bayesian networks reasoning platform GeNIe. The result shows that the diagnosis effect is more comprehensive and reasonable than the other method.

Conceptual Issues in the Qualification of Intelligent Buildings

The reality of global warming must have been settled by now while the incidence of same has in very recent times adopted unprecedented dimensions. The global community continues to look for ways to combat the impact of climate change and technology is looked upon to deliver the innovations that would ensure a better tomorrow today. Rapid advancement of Information Technology (IT), is now transforming the way we create and interact with the built environment with the notion of Intelligent Buildings (IBs) underscoring its main features. However, these IBs utilize systems that require energy, and fossil fuels are currently the world’s primary energy sources;they can also irreparably harm the environment, exacerbating climate change. What then is the true essence of IBs? This paper, through review of existing literature, attempts to explore some issues associated with the conceptualization of IBs, highlighting how they are similar with other notional options that deliver the same benefits but without the needed IT systems or the energy required in running them. It also discusses the need to focus on less energy demanding and management approaches at design or occupancy of buildings as a way to reduce the demand and thus consumption of fossil fuels across the world.

Development of intelligent buildings in Bahrain

There is a growing demand for high building performance,providing better energy efficiency as well as high standard living and workplace. Intelligent Buildings (IBs) will meet the needs of sustainable development in built environment. The Kingdom of Bahrain's construction industry has grown significantly in past years to support economic growth,other business sectors,and the aim to be one of the world's major financial centres. This paper aims at investigating current issues regarding intelligent buildings in the Kingdom of Bahrain. Case studies of three buildings,which are Bahrain Financial Harbour (BFH),Bahrain World Trade Centre (BWTC) Project and the Bahrain City Centre (BCC) Shopping Mall,have been carried out via structured observation,interview and questionnaire survey in Bahrain in 2007. Through this study,we conclude that the pace of construction in Bahrain and the Middle East is such that there are lots of scopes for IBs to develop further,both from the perspective of the number of IBs being built and also the sophistication of their specifications.

Design of Multi-Sensors Cooperation Control System for Intelligent Building

This paper presents a design of intelligent building control system based on multi-sensors. In order to achieve comfort, low carbon and energy conservation for buildings. The design uses STC89C52 chip, combined with monitoring data of Pyroelectric infrared microwave dual sensor, temperature sensors and light sensors to control the optical system, the temperature control system and the security system. It helps to achieve low carbon and energy conservation. In addition, the energy-saving effect of a medium-sized multimedia classroom was analyzed. We analyze the feasibility of the system. It is proved that the system is low cost, high yield and easy to operate, with strong engineering application value.

Application of Intelligent Technology in Building Electrical Lighting Project

The rapid development of intelligent technology has led to its introduction into the field of electrical lighting in buildings.It provides more technical support for system design,use,and management,and creates a comfortable and safe living environment.The adoption of intelligent technology enables the creation of an intelligent management system,where controllers and sensors are used to adjust the light source within the building,monitor and manage the lighting system in real time,monitor the energy consumption and safety of the system,and achieve the goal of energy saving and emission reduction.This paper briefly discusses the application and significance of intelligent technology in electrical lighting and puts forward design ideas to optimize electrical lighting and measures for lighting system management.

Discussion on the Intelligent Design of Ultra-Low Energy Consumption Passive Buildings

With the continuous development of science and technology and the gradual improvement of modem building technology, people pay more and more attention to the introduction of advanced technology in architectural design, such as the application of intelligent technology. With the increasingly severe environmental situation, people are increasingly demanding the environmental performance and green performance of buildings. The establishment of ultra-low energy consumption passive buildings has become one of the key construction contents of construction projects. This paper mainly analyzes the design points and architectural forms of related buildings from the perspective of intelligent control.

Design of the University Building Corridor Intelligent Lighting Control System

This paper introduces the traditional lighting control mode and analyzes of defects in three ways, so this paper puts forward four kinds of working mode of intelligent lighting control system. Combined with the working pattern, this paper designs an intelligent lighting control system to analyze the application advantages of intelligent system.

Deep Learning for Multivariate Prediction of Building Energy Performance of Residential Buildings

In the quest to minimize energy waste,the energy performance of buildings(EPB)has been a focus because building appliances,such as heating,ventilation,and air conditioning,consume the highest energy.Therefore,effective design and planning for estimating heating load(HL)and cooling load(CL)for energy saving have become paramount.In this vein,efforts have been made to predict the HL and CL using a univariate approach.However,this approach necessitates two models for learning HL and CL,requiring more computational time.Moreover,the one-dimensional(1D)convolutional neural network(CNN)has gained popularity due to its nominal computa-tional complexity,high performance,and low-cost hardware requirement.In this paper,we formulate the prediction as a multivariate regression problem in which the HL and CL are simultaneously predicted using the 1D CNN.Considering the building shape characteristics,one kernel size is adopted to create the receptive fields of the 1D CNN to extract the feature maps,a dense layer to interpret the maps,and an output layer with two neurons to predict the two real-valued responses,HL and CL.As the 1D data are not affected by excessive parameters,the pooling layer is not applied in this implementation.Besides,the use of pooling has been questioned by recent studies.The performance of the proposed model displays a comparative advantage over existing models in terms of the mean squared error(MSE).Thus,the proposed model is effective for EPB prediction because it reduces computational time and significantly lowers the MSE.

基于BIM技术与模拟退火算法的村镇轻钢框架结构智能设计方法

传统村镇住宅结构设计需要进行大量的人工试算与重复建模,而受制于建设成本,村镇住宅无法像城镇住宅一样通过设计师进行专业的结构设计与验算,其安全性与经济性均难以满足要求。为此,提出一种村镇轻钢框架结构智能设计方法,包括智能建模与智能优化两个环节。基于图层自动识别算法、光学字符识别技术、自适应分块算法提出村镇轻钢框架结构BIM智能建模方法,包括图层识别、轴文本数据提取、墙体轮廓提取等,智能建模结果基本满足实际工程要求。基于提出的两阶段模拟退火算法给出村镇轻钢框架结构的智能优化方法,优化速度较快,优化效果良好。通过实际工程案例对提出的智能设计方法进行验证,结果表明,提出的村镇轻钢框架结构智能设计方法具有可行性,与传统的人工设计方法相比,设计周期可缩短70%以上,材料用量、结构设计指标接近人工设计结果。

迈向智能监察:人工智能赋能国家监察的逻辑与进路

新一代人工智能的兴起为国家治理注入新动能,为国家监察工作的数字化、智能化指明方向。人工智能赋能国家监察具有以“数据全覆盖”实现“监察全覆盖”、从人力监督到智能监督等现实价值。受限于国家监察的初创性与人工智能的局限性,国家监察智能化呈现阶段性特征。国家监察的智能化发展围绕数据、算法、算力三大核心要素,实现监察“块数据”构建、面向国家监察的语言模型嵌入及算力资源的优化供给。针对人工智能存在的数据隐私、数据安全等技术性风险,可从人工智能政府采购的制度化与规范化、建构监察对象数据隐私与安全保护机制和人工智能监察应用的纠错与救济机制等方面予以防范和化解。

大语言模型的技术应用前景与风险挑战

针对大语言模型(LLM)技术的快速发展,剖析它的技术应用前景和风险挑战,对通用人工智能(AGI)的发展和治理有重要参考价值。首先,以Multi-BERT(Multilingual Bidirectional Encoder Representations from Transformers)、GPT(Generative Pre-trained Transformer)和ChatGPT(Chat Generative Pre-Trained Transformer)等语言模型为代表,综述LLM的发展脉络、核心技术和评估体系;其次,分析LLM现存的技术局限和安全风险;最后,提出LLM在技术上改进、政策上跟进的建议。分析指出作为发展阶段的LLM,现有模型存在非真实性及偏见性输出、实时自主学习能力欠缺,算力需求庞大,对数据质量和数量依赖性强,语言风格单一;存在数据隐私、信息安全和伦理等方面的安全风险。未来发展可从技术上继续改进,从“大规模”转向“轻量化”、从“单模态”走向“多模态”、从“通用”迈入“垂类”;从政策上实时跟进,实施有针对性的监管措施,规范应用和发展。

常态化监管体系下医保智能监控应用现状及优化策略研究

常态化监管体系下,面对医保监管对象众多、资金量庞大、结算数据海量的新形势、新挑战,医保智能监控成为基金监管的必备工具、重要手段及技术支撑。本文通过梳理回顾国家医保局成立以来的常态化监管新举措,分析医保智能监控的必要性和意义;以某省(市)为例,应用专家访谈法及问卷调查法调查统筹区医保经办机构的智能监控手段应用现状;提出构建我国医保智能监控体系及推进地区应用的优化策略。

广东省东莞市生猪及其产品质量安全信息化监管模式

为解决猪肉产品消费环节与生猪养殖环节信息脱钩的问题,东莞市以数字喷码技术为基础,探索建立了生猪及其产品质量安全信息化监管模式,打通了从生猪养殖到猪肉产品消费各环节的信息关联,实现了生猪屠宰及肉产品质量安全可追溯和全产业链智慧监管。经东莞市2个生猪屠宰场及4个农贸市场试点证实,该模式可行有效,既节省了屠宰加工企业经营成本,又提高了肉产品价值,同时也提高了监管机构监管效率,使动物检疫行为更加规范,动物疫病防控能力得到增强,保障了东莞市猪肉肉产品质量卫生安全。东莞市的全过程信息化监管模式为其他地区的生猪产品信息化监管提供了借鉴。

在强国建设中彰显大外作为

人才培养在中华民族伟大复兴进程中占据突出地位,也是建设中国特色社会主义教育强国的核心议题。本文从落实立德树人根本任务、重构大学外语课程体系、推进人工智能赋能大学外语教学三个方面论述大学外语教育在强国建设中的担当作为。

新形势下MDT监管模式在清廉医院建设中的实践

在全国范围内开展医药领域腐败问题集中整治工作的新形势下,浙江大学医学院附属儿童医院纪检监察室借鉴多学科行政管理模式,创建了以清廉科室、行风查房为抓手的MDT监管模式,推进落实党风廉政建设党委主体责任和纪委的监督责任,通过查摆问题、督促整改、完善制度等方式实现全流程闭环管理。在强化责任体系建设、廉洁风险防控、强化行风建设、精准廉政宣教等方面取得良好成效。