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ABSTRACT: The photovoltaic (PV) system is considered an unlimited source of clean energy, whose amount of electricity generation changes according to the monthly average daily solar radiation (MADSR). It is revealed that the MADSR distribution in South Korea has very diverse patterns due to the country's climatic and geographical characteristics. This study aimed to develop a MADSR estimation model for the location without the measured MADSR data, using an advanced case based reasoning (CBR) model, which is a hybrid methodology combining CBR with artificial neural network, multi-regression analysis, and genetic algorithm. The average prediction accuracy of the advanced CBR model was very high at 95.69%, and the standard deviation of the prediction accuracy was 3.67%, showing a significant improvement in prediction accuracy and consistency. A case study was conducted to verify the proposed model. The proposed model could be useful for owner or construction manager in charge of determining whether or not to introduce the PV system and where to install it. Also, it would benefit contractors in a competitive bidding process to accurately estimate the electricity generation of the PV system in advance and to conduct an economic and environmental feasibility study from the life cycle perspective.
Environmental Science & Technology 04/2013; · 4.80 Impact Factor
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ABSTRACT: The number of deteriorated multi-family housing complexes in South Korea continues to rise, and consequently their electricity consumption is also increasing. This needs to be addressed as part of the nation's efforts to reduce energy consumption. The objective of this research was to develop a decision support model for determining the need to improve multi-family housing complexes. In this research, 1664 cases located in Seoul were selected for model development. The research team collected the characteristics and electricity energy consumption data of these projects in 2009-2010. The following were carried out in this research: (i) using the Decision Tree, multi-family housing complexes were clustered based on their electricity energy consumption; (ii) using Case-Based Reasoning, similar cases were retrieved from the same cluster; and (iii) using a combination of Multiple Regression Analysis, Artificial Neural Network, and Genetic Algorithm, the prediction performance of the developed model was improved. The results of this research can be used as follows: (i) as basic research data for continuously managing several energy consumption data of multi-family housing complexes; (ii) as advanced research data for predicting energy consumption based on the project characteristics; (iii) as practical research data for selecting the most optimal multi-family housing complex with the most potential in terms of energy savings; and (iv) as consistent and objective criteria for incentives and penalties.
Journal of Environmental Management 08/2012; 112:67-78. · 3.24 Impact Factor
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ABSTRACT: Green-roof systems offer various benefits to man and nature, such as establishing ecological environments, improving landscape and air quality, and offering pleasant living environments. This study aimed to develop an optimal-scenario selection model that considers both the economic and the environmental effect in applying GRSs to educational facilities. The following process was carried out: (i) 15 GRSs scenarios were established by combining three soil and five plant types and (ii) the results of the life cycle CO(2) analyses with the GRSs scenarios were converted to an economic value using certified emission reductions (CERs) carbon credits. Life cycle cost (LCC) analyses were performed based on these results. The results showed that when considering only the currently realized economic value, the conventional roof system is superior to the GRSs. However, the LCC analysis that included the environmental value, revealed that compared to the conventional roof system, the following six GRSs scenarios are superior (cost reduction; reduction ratio; in descending order): scenarios 13 ($195,229; 11.0%), 3 ($188,178; 10.6%), 8 ($181,558; 10.3%), 12 ($130,464; 7.4%), 2 ($124,566; 7.0%), and 7 ($113,931; 6.4%). Although the effect is relatively small in terms of cost reduction, environmental value attributes cannot be ignored in terms of the reduction ratio.
Environmental Science & Technology 07/2012; 46(15):8475-83. · 4.80 Impact Factor
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Expert Syst. Appl. 01/2011; 38:2797-2808.
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Expert Syst. Appl. 01/2011; 38:8597-8606.
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ABSTRACT: In a high-rise building project that involves many repetitive construction processes, the effective control of such repetitive construction processes is a key factor in the success of the project. Unlike the existing scheduling methods for repetitive construction processes, a scheduling model that considers (i) the flexible job logic of the multiple work tasks that comprise a construction process and (ii) the productivity of the construction equipment and labor was developed in this paper. Various theories and algorithms such as the linking dummy, the linear scheduling method, and the production rate, were implemented in the development of the model. A scheduling model was then proposed based on such theories and algorithms and on a mathematical formula. The proposed model was verified by applying it to core wall construction, a key repetitive process in a high-rise building project. Verification showed that the developed model exhibited over 90% reliability. It is expected that the proposed model will allow effective scheduling for repetitive construction processes with flexible job logic.Un projet d'immeuble de grande hauteur impliquant plusieurs procédés de construction répétitifs, le contrôle efficace de ces procédés de construction répétitifs est un facteur clé du succès de ce projet. Contrairement aux méthodes à calendriers existantes pour les procédés de construction répétitifs, un modèle de calendrier qui tient compte de (i) la logique d'emploi flexible pour des tâches de travail multiples qui comprennent un procédé de construction et (ii) de la productivité des équipements et de la main-d'œuvre de construction a été développé dans cet article. Diverses théories et divers algorithmes, tels que les liens vides, la méthode de calendrier linéaire et le taux de production, ont été implantés lors du développement du modèle. Un modèle de calendrier a ensuite été proposé basé sur de tels algorithmes et théories et sur une formule mathématique. Le modèle proposé a été vérifié en l'utilisant pour la construction d'un mur écran, un procédé répétitif clé dans un projet d'immeuble de grande hauteur. Une vérification a indiqué que le modèle développé présentait une fiabilité de plus de 90 %. Le modèle proposé devrait permettre un calendrier efficace pour les procédés de construction répétitifs avec une logique d'emploi flexible.
Canadian Journal of Civil Engineering 12/2010; 38(1):36-48. · 0.33 Impact Factor
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Expert Syst. Appl. 01/2009; 36:10461-10470.
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ABSTRACT: According to the United Nations Framework Convention on Climate Change (UNFCCC), there are thirty countries, mostly advanced countries, designated as countries for Mandatory Greenhouse Gas Reduction. Korea will mostly likely be included in these countries based on the second phase of the mandatory reduction scheme, which starts in 2013. Efforts have been exerted to reduce greenhouse gas both locally and abroad, focusing on reducing building energy as part of the greenhouse gas reduction plan.This study proposes a maintenance management process for reducing CO2 in shopping mall complexes. The proposed process, which is composed of four steps, focuses on producing the facility improvement scenarios that can reduce energy through facility maintenance management. This study verifies the proposed maintenance management process by applying it to two shopping mall complexes currently in operation and creates the facility improvement scenarios for both malls. The proposed process may also be used to generate an improvement scenario for other facilities.
Energy and Buildings 43(4):894-904. · 2.39 Impact Factor
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ABSTRACT: Value Engineering (VE) studies on a number of facilities have been carried out for half a century now since the initial application of VE to the construction field. As a result, many VE proposals (VEPs) have been produced and applied. “VEPs” refer to groups of creative and innovative ideas produced by experts in various fields based on their experiences, knowledge, and situation analyses. The construction industry, however, has not exerted enough effort to systemically accumulate and use such knowledge. Thus, there is a need to increase the productivity of VE study under the present circumstances.In this study, RETRIEVE (REmembering Tool for Reusing the Ideas Evolved in Value Engineering), a system designed to (i) capture ideas from the past VE study cases for use in solving the current problems and improving the current situations; and to (ii) support the development of a VEP, was developed. To develop RETRIEVE, the information and knowledge that had been included in VEPs were classified, and a case library was constructed based on the establishment of their expression types. In addition, a matching algorithm and a ranking algorithm for retrieving past VEP cases, which are helpful in addressing the current problems, were developed. Case studies were carried out to validate the usability of the system, and the adequacy of the method for weight assignment was verified.
Automation in Construction 18(8):1123-1134. · 1.50 Impact Factor
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ABSTRACT: Most past studies that analyze project performance and the characteristics that affect such performance consist of a simple form, in which they present the brief relationship between project performance and a few characteristics that affect it. Furthermore, due to the limitations of the research methodologies used in these studies, important characteristics were often not considered in developing the relationship between project performance and project characteristics. This study aims to analyze the overall relationship between project performance and a project’s characteristics. This study deduced (i) the overall causal relationship and (ii) the degree of influence between 17 project characteristics and five project performance indices. In order to achieve this goal, this study employed the factor analysis method and a structural equation model (SEM). In addition, this study established a SEM based on quantitative data from actual case studies as opposed to previous SEM studies that mainly use qualitative data.The SEM developed in this study can identify the project characteristics that affect the level of project performance required by owner in the planning stage, and is thus expected to help facilitate the decision-making process in the early planning stage of a project.
Expert Systems with Applications.
