• Smart Structures and Systems
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• v.21 no.1
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• pp.123-137
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• 2018

Structural monitoring is the most important part of the construction and operation of the embankment dams. Appropriate instruments selection for dams is vital, as inappropriate selection causes irreparable loss in critical condition. Due to the lack of a systematic approach to determine adequate instruments, a framework based on three comparable Multi-Attribute Decision Making (MADM) methods, which are VIKOR, technique of order preference by similarity to ideal solution (TOPSIS) and Preference ranking organization method for enrichment evaluation (PROMETHEE), has been developed. MADM techniques have been widely used for optimizing priorities and determination of the most suitable alternatives. However, the results of the different methods of MADM have indicated inconsistency in ranking alternatives due to closeness of judgements from decision makers. In this study, 9 criteria and 42 geotechnical instruments have been applied. A new method has been developed to determine the decision makers' importance weights and an aggregation method has been introduced to optimally select the most suitable instruments. Consequently, the outcomes of the aggregation ranking correlate about 94% with TOPSIS and VIKOR, and 83% with PROMETHEE methods' results providing remarkably appropriate prioritisation of instruments for embankment dams.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.9
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• pp.3293-3311
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• 2015

Cloud services are required to be composed as a single service to fulfill the workflow applications. Service composition in Cloud raises new challenges caused by the diversity of users with different QoS requirements and vague preferences, as well as the development of cloud computing having geographically distributed characteristics. So the selection of the best service composition is a complex problem and it faces trade-off among various QoS criteria. In this paper, we propose a Cloud service composition approach based on evolutionary algorithms, i.e., NSGA-II and MOPSO. We utilize the combination of multi-objective evolutionary approaches and Decision-Making method (AHP) to solve Cloud service composition optimization problem. The weights generated from AHP are applied to the Crowding Distance calculations of the above two evolutionary algorithms. Our algorithm beats single-objective algorithms on the optimization ability. And compared with general multi-objective algorithms, it is able to precisely capture the users' preferences. The results of the simulation also show that our approach can achieve a better scalability.

• Journal of Construction Engineering and Project Management
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• v.4 no.3
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• pp.53-59
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• 2014

Project managers are responsible to conduct project on time with least amount of costs and the most possible quality with respect to shortage of resources and environmental certainties. They have to make the best decision to reach such conflicting objects. In this study the project scheduling with multi goals-multi modes was planned in fuzzy conditions under resource constraints and expanded by fuzzy goal programing (FGP). The project cost was calculated by the price of renewable resources and the quality criteria were evaluated by the quality function deployment method (QFD). Finally the model was verified by a construction case study with 22 activities along with solving by GAMS. The results showed that this model could provide a systematic framework to facilitate the decision making process and made the project managers to be able to schedule the project closer to reality.

• Earthquakes and Structures
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• v.17 no.2
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• pp.205-219
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• 2019

In Peru, construction of dwellings using confined masonry walls (CM) has a high percentage of acceptance within many sectors of the population. It is estimated that only in Lima, 80% of the constructions use CM and at least 70% of these are informal constructions. This mean that they are built without proper technical advice and generally have a high seismic vulnerability. One way to reduce this vulnerability is by reinforcing the walls. However, despite the existence of some reinforcement methods in the market, not all of them can be applied massively because there are other parameters to take into account, as economical, criteria for seismic improvement, reinforcement ratio, etc. Therefore, in this paper the feasibility of using five reinforcement techniques has been studied and compared. These reinforcements are: welded mesh (WM), glass fiber reinforced polymer (GFRP), carbon fiber reinforced polymer (CFRP), steel bar wire mesh (CSM), steel reinforced grout (SRG). The Multi-Criteria Decision Making (MCDM) method can be useful to evaluate the most optimal strengthening technique for a fast, effective and massive use plan in Peru. The results of using MCDM with 10 criteria indicate that the Carbon Fiber Reinforced Polymer (CFRP) and Steel Reinforced Grout (SRG) methods are the most suitable for a massive reinforcement application in Lima.

• Land and Housing Review
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• v.13 no.3
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• pp.107-113
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• 2022

With increasing airtight building construction aimed at reducing energy consumption, indoor relative humidity is increasing which can lead to condensation and moisture damage in multi-family residential buildings. This has led to increased implementation of mechanical ventilation to control indoor moisture. However mechanical ventilation systems consume additional energy and generate noise. As this leads to occupant discomfort, it is necessary to select a ventilation system that addresses the energy and noise issues. This research measured the ventilation performance, energy consumption, and noise level of mechanical ventilation devices in multi-family residential buildings. TOPSIS, a multi-criteria decision making technique was used to determine appropriate ventilation strategies in addition to occupant ventilation system operation preference.

• Journal of Korea Water Resources Association
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• v.50 no.2
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• pp.121-128
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• 2017

In this study, robustness index and uncertainty analysis were proposed to quantify the risk inherent in the process of climate change vulnerability assessment. The water supply vulnerability for six metropolitan cities (Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan), except for Seoul, were prioritized using TOPSIS, a kind of multi-criteria decision making method. The robustness index was used to analyze the possibility of rank reversal and the uncertainty analysis was introduced to derive the minimum changed weights of the criteria that determine the rank reversal between any paired cities. As a result, Incheon and Daegu were found to be very vulnerable and Daegu and Busan were derived to be very sensitive. Although Daegu was relatively vulnerable against the other cities, it can be largely improved by developing and performing various climate change adaptation measures because it is more sensitive. This study can be used as a preliminary assessment for establishing and planning climate change adaptation measure.

• Journal of Intelligence and Information Systems
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• v.12 no.3
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• pp.15-32
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• 2006

The increasing complexity of the socio-economic environments makes it less and less possible for single decision-maker to consider all relevant aspects of problem. Therefore, many organizations employ groups in decision making. In this paper, we present a multiperson decision making method using fuzzy logic with linguistic quantifier when each of group members specifies imprecise judgments possibly both on performance evaluations of alternatives with respect to the multiple criteria and on the criteria. Inexact or vague preferences have appeared in the decision making literatures with a view to relaxing the burdens of preference specifications imposed to the decision-makers and thus taking into account the vagueness of human judgments. Allowing for the types of imprecise judgments in the model, however, makes more difficult a clear selection of alternative(s) that a group wants to make. So, further interactions with the decision-makers may proceed to the extent to compensate for the initial comforts of preference specifications. These interactions may not however guarantee the selection of the best alternative to implement. To circumvent this deadlock situation, we present a procedure for obtaining a satisfying solution by the use of linguistic quantifier guided aggregation which implies fuzzy majority. This is an approach to combine a prescriptive decision method via a mathematical programming and a well-established approximate solution method to aggregate multiple objects.

• Smart Structures and Systems
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• v.15 no.6
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• pp.1583-1600
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• 2015

When natural disasters occur, including earthquakes, tsunamis, and debris flows, they are often accompanied by various types of damages such as the collapse of buildings, broken bridges and roads, and the destruction of natural scenery. Natural disaster detection and warning is an important issue which could help to reduce the incidence of serious damage to life and property as well as provide information for search and rescue afterwards. In this study, we propose a novel computer vision technique for debris flow detection which is feature-based that can be used to construct a debris flow event warning system. The landscape is composed of various elements, including trees, rocks, and buildings which are characterized by their features, shapes, positions, and colors. Unlike the traditional methods, our analysis relies on changes in the natural scenery which influence changes to the features. The "background module" and "monitoring module" procedures are designed and used to detect debris flows and construct an event warning system. The multi-criteria decision-making method used to construct an event warring system includes gradient information and the percentage of variation of the features. To prove the feasibility of the proposed method for detecting debris flows, some real cases of debris flows are analyzed. The natural environment is simulated and an event warning system is constructed to warn of debris flows. Debris flows are successfully detected using these two procedures, by analyzing the variation in the detected features and the matched feature. The feasibility of the event warning system is proven using the simulation method. Therefore, the feature based method is found to be useful for detecting debris flows and the event warning system is triggered when debris flows occur.

• Journal of the Korean Society for Railway
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• v.12 no.2
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• pp.291-301
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• 2009

This paper presents the optimal design and analysis method of the train overhaul maintenance facility based on the simulation. Because the train is composed of a coach or more, we design the simulation model after analyzing the operation of train into train, coach, coach's body parts and wheel parts and soon. In simulation analysis, we consider the critical (dependent) factors and design (independent) parameters for the selection of alternatives and optimal design. Therefore, Multi Criteria Decision Making (MCDM) is proposed for the selection of alternatives and optimal method in order to find the optimal design factors. The case study for the above approach is used for the electronic locomotive overhaul maintenance facility. This paper provides a comprehensive framework for the train overhaul maintenance facility design using the simulation, MCDM and optimal methods. Therefore, the method developed for this research can be adopted for other enhancements in different but comparable situation.

• Journal of applied mathematics & informatics
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• v.41 no.5
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• pp.973-988
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• 2023

In real-life scenarios, we may have to deal with real numbers or numbers in intervals or a combination of both to solve multi-criteria decision-making (MCDM) problems. Also, we may come across a situation where we must combine this interval and actual number membership values into a single real number. The most significant factor in combining these membership values into a single value is by using aggregation operators or scoring algorithms. To overcome such a situation, we suggest the cubic hypersoft set (CHSS) concept as a workaround. Ultimately, this makes it simple for the decision-maker to obtain information without misconceptions. The primary aim of this study is to establish some operational laws for the cubic hypersoft set, present the fundamental properties of aggregation operators and propose an algorithm by using the technique of order of preference by similarity to the ideal solution (TOPSIS) technique based on correlation coefficients to analyze the stress-coping skills of workers.