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.

无线传感器网络在智能建筑中的优化实现与评估(英文)

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.

Employing Computational Intelligence to Generate More Intelligent and Energy Efficient Living Spaces

Our living environments are being gradually occupied with an abundant number of digital objects that have networking and computing capabilities. After these devices are plugged into a network, they initially advertise their presence and capabilities in the form of services so that they can be discovered and, if desired, exploited by the user or other networked devices. With the increasing number of these devices attached to the network, the complexity to configure and control them increases, which may lead to major processing and communication overhead. Hence, the devices are no longer expected to just act as primitive stand-alone appliances that only provide the facilities and services to the user they are designed for, but also offer complex services that emerge from unique combinations of devices. This creates the necessity for these devices to be equipped with some sort of intelligence and self-awareness to enable them to be self-configuring and self-programming. However, with this ＂smart evolution＂, the cognitive load to configure and control such spaces becomes immense. One way to relieve this load is by employing artificial intelligence （AI） techniques to create an intelligent ＂presence＂ where the system will be able to recognize the users and autonomously program the environment to be energy efficient and responsive to the user＇s needs and behaviours. These AI mechanisms should be embedded in the user＇s environments and should operate in a non-intrusive manner. This paper will show how computational intelligence （CI）, which is an emerging domain of AI, could be employed and embedded in our living spaces to help such environments to be more energy efficient, intelligent, adaptive and convenient to the users.

Microbial self-healing of cracks in cement-based materials and its influencing factors

Cement-based materials are brittle and crack easily under natural conditions.Cracks can reduce service life because the transport of harmful substances can cause corrosion damage to the structures.This review discusses the feasibility of using microbial self-healing agents for crack healing.Tubular and spherical carriers can be used to load microbial self-healing agents and protect microbes,which prolongs the self-healing time.The area self-healing ratio,permeability,mechanical strength,precipitation depth method,numerical modeling,and ultrasonic method can be employed to identify the self-healing effect of cracks.Moreover,the self-healing mechanism is systematically analyzed.The results showed that microbial self-healing agents can repair cracks in cement-based materials in underground projects and dam gates.The difficulties and future development of self-healing cracks were analyzed.A microbial selfhealing agent was embedded in the cement-based material,which automatically repaired the developing cracks.With the development of intelligent building materials,self-healing cracks have become the focus of attention.

Huayou Cobalt Invest RMB 6.3 billion to Build an Intelligent Manufacturing Base

Huayou Cobalt announced on the evening of March 12 that the company(or its subsidiary)plans to invest in the construction of an intelligent manufacturing base for new energy materials(an annual 150,000-ton ternary precursor material project for lithium batteries).The total investment in the project is