به نام خدا
Title: Indoor Air Quality Control for Energy-Efficient Buildings Using CO 2 Predictive Model
Authors: Zhu Wang and Lingfeng Wang
Abstract: In this paper, an intelligent control system for indoor air quality in energy-efficient buildings is proposed. The goal of intelligent air quality control for energy-efficient buildings is to maintain the indoor CO 2 concentration in the comfort zone with a minimum amount of energy consumption. In this study, the CO 2 concentration is used as the indicator of indoor air quality and a CO 2 predictive model is utilized to forecast the indoor CO2 concentration. Particle swarm optimization (PSO) is applied to derive the optimal ventilation rate. As compared with the traditional ON/OFF ventilation control system, the performance of the proposed intelligent control system has demonstrated its advantage in terms of energy savings. A case study and corresponding simulation results are detailed in the paper.
Publish Year: 2012
Published in: INDIN - IEEE
Number of Pages: 6
موضوع: کنترل کیفیت (Quality Control )
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به نام خدا
Title: Function optimisation by learning automata
Authors: QH Wu , HL Liao
Abstract: This paper presents a new algorithm, Function Optimisation by Learning Automata (FOLA), to solve complex function optimisation problems. FOLA consists of multiple automata, in which each automaton undertakes dimensional search on a selected dimension of the solution domain. A search action is taken on a path which is identified in the search space by the path value, and the path value is updated using the values of the states visited in the past, via a state memory that enables better use of the information collected in the optimisation process. In this paper, FOLA is compared with two popularly used particle swarm optimisers and four newly-proposed optimisers, on nine complex multi-modal benchmark functions. The experimental results have shown that in comparison with the other optimisers, FOLA offers better performance for most of the benchmark functions, in terms of its convergence rate and accuracy, and it uses much less computation time to obtain accurate solutions, especially for high-dimensional functions. In order to explore the FOLA s potential for applications, it is also applied to solve an optimal power flow problem of power systems. FOLA is able to minimise the fuel cost and enhance the voltage stability of the power system more efficiently in comparison with the other algorithms.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 20
موضوع: اتوماتای یادگیر (Learning Automata )
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به نام خدا
Title: Augmenting the World using Semantic Web Technologies
Authors: Jens Grubert, Lyndon Nixon, Gerhard Reitmayr
Abstract: Creating and maintaining augmented scenes for mobile Augmented Reality browsers can be a challenging and time consuming task. The timeliness of digital information artifacts connected to changing urban environments require authors to constantly update the structural representations of augmented scenes or to accept that the information will soon be outdated. We present an approach for retrieving multimedia content and relevant web services for mobile Augmented Reality applications at runtime. Using semantic web technologies we are able to postpone the retrieval of actual media items to the moment a user actually perceives an augmented scene. This allows content creators to augment a scene only once and avoid continuous manual updates. We also discuss the tradeoff between runtime content retrieval using Linked Data concepts and decreased control over the scene appearance at the time of authoring that comes along with this approach.
Publish Year: 2012
Published in: ISMAR - IEEE
Number of Pages: 3
موضوع: وب معنایی (Semantic Web )
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به نام خدا
Title: A high abstraction level approach for detecting feature interactions between telecommunication services
Authors: Zohair Chentouf, Ahmed Khoumsi
Abstract: When several telecommunication services are running at the same time, undesirable behaviors may arise, which are commonly called feature interactions. Several methods have been developed for detecting and resolving feature interactions. However, most of these methods are based on detailed models of services, which make them suffer from state space explosion. Moreover, different telecommunication operators cannot cooperate to manage feature interactions by exchanging detailed service models because this violates the confidentiality principle. Our work is a part of the few attempts to develop feature interaction detection methods targeting to avoid or reduce significantly state space explosion. In order to reach this objective, we first develop a so called Cause Restrict language to model subscribers of telecommunication services at a very high abstraction level. A Cause Restrict model of a subscriber provides information such as: what is the cause of what, and what restricts (or forbids) what, and specifies coarsely the frequency of each operation cause or restrict by always or sometimes. Then, we develop a method that detects feature interactions between telecommunication services modeled in the Cause Restrict language. We demonstrate the applicability of our approach by modeling several services and detecting several feature interactions between them. New feature interactions have been detected by our approach.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 17
موضوع: مخابرات (Telecommunication)
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