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Öğe Application of time series models for heating degree day forecasting(De Gruyter Open Ltd, 2020) Kuru M.; Calis G.This study aims at constructing short-term forecast models by analyzing the patterns of the heating degree day (HDD). In this context, two different time series analyses, namely the decomposition and Box–Jenkins methods, were conducted. The monthly HDD data in France between 1974 and 2017 were used for analyses. The multiplicative model and 79 SARIMA models were constructed by the decomposition and Box–Jenkins method, respectively. The performance of the SARIMA models was assessed by the adjusted R2 value, residual sum of squares, the Akaike Information Criteria, the Schwarz Information Criteria, and the analysis of the residuals. Moreover, the mean absolute percentage error, mean absolute deviation, and mean squared deviation values were calculated to evaluate the performance of both methods. The results show that the decomposition method yields more acceptable forecasts than the Box–Jenkins method for supporting short-term forecasting of the HDD. © 2020 Kuru and Calis, published by Sciendo.Öğe A comparative study for layout planning of temporary construction facilities: Optimization by using ant colony algorithms(Nottingham, 2019) Calis G.; Yuksel O.Construction site layout is among the most challenging tasks of the construction planning process that consists of identifying temporary facilities to support construction activities, defining their shapes, sizes and allocating them into available spaces within the site boundaries. A good site layout can minimize the travel time between facilities, improve site safety, increase productivity, and, thus, decrease construction cost and time. Although site layout has such a major role in planning, it has received relatively little attention due to the complex nature of the problem, which is formulated as a combinatorial optimization problem. In this study, the Ant Colony Optimization (ACO) algorithm is proposed for site layout problems. ACO mimics the behavior of real ants for finding solutions and is proved to introduce feasible solutions for combinatorial optimization problems. The effectiveness of proposed algorithm is illustrated by using a literature problem. It was observed that the developed ACO model performed a better layout alternative. © 2018 Esprit. All rights reserved.Öğe An improved grey Verhulst model to forecast energy demand in the USA and Turkey(ICE Publishing, 2022) Atalay S.D.; Calis G.; Adiyaman M.The importance of accurate energy demand modelling has increased to support the decision making of policymakers for ensuring a safe energy supply. However, forecasting energy demand has several difficulties due to the complexity of the supply line, demand increase, non-linearity of data and volatility of energy usage. In this study, an improved grey Verhulst model with a constant term (GVMCT), which is based on the grey model, is introduced for improving the accuracy of energy demand prediction models. Within this context, the total residential electricity demand of both the USA and Turkey is modelled by way of linear and quadratic trend models, as well as three grey models, including the proposed GVMCT model. The effectiveness of the models is assessed based on the mean absolute error (MAE), mean squared error and root mean square error. The results show that the linear trend is the best-performing model, with an MAE of 34 564.81844, for the US data, whereas the proposed GVMCT, with an MAE of 4130.086917, outperforms all models for the data of Turkey. © 2022 ICE Publishing: All rights reserved.Öğe Investigating the link between CO2 concentration, thermal comfort and occupant perception in educational buildings(The Society for Modeling and Simulation International, 2018) Kuru M.; Calis G.Thermal comfort conditions, as well as CO2 concentration in educational buildings, indirectly affect students’ attention, comprehension and learning performance. Although the standards recommend thresholds for both thermal comfort conditions and CO2 concentrations in indoor environments, the perception of students might also affect their performance. This study aims at understanding the relationship between students’ perception towards existing conditions and actual measurements. A university building, which is located in the Mediterranean climatic region of Turkey, was selected as a test site. CO2 concentration, indoor air temperature, mean radiant temperature, relative humidity and air velocity were monitored for ten days in the heating season. In addition, a survey study was conducted to understand the perception of occupants. Predicted Mean Votes (PMV) were calculated to assess the thermal comfort conditions of the classroom whereas CO2 concentrations were evaluated according to ASHRAE Standard 62.1-2016. The correlation between PMV values and CO2 concentrations were analyzed via Pearson correlation coefficient. Moreover, the effects of occupants’ thermal sensation, relative humidity and air velocity perceptions on the CO2 perception were analyzed via cross-tabulation and chi-square independence tests. The main results show that: (1) 53% of measurements exceed the recommended target value of 1000 ppm by ASHRAE, (2) there is a strong positive correlation between PMV values and CO2 concentration, (3) CO2 perception of occupants are influenced by thermal sensation as well as relative humidity and air velocity perceptions. © 2018 Society for Modeling & Simulation International (SCS).Öğe Investigation of using fuzzy logic to model occupant satisfaction and behavior in a building(CEUR-WS, 2015) Calis G.; Goktepe A.B.; Bayram I.Occupant satisfaction with indoor environmental conditions are in close relation to energy consumption in buildings. Despite the increasing efforts to maintain thermal comfort conditions in buildings with control strategies, occupants are not usually satisfied, and, thus, change their behavior which generally interfere with building operation systems. Therefore, modeling and characterizing occupant satisfaction and behavior are important considerations in the building energy use. However, occupant satisfaction and behavior as well as indoor environmental conditions have serious amount of uncertainty, and, thus, it is difficult to simulate them via traditional techniques. In this study, a total of 8 tests were conducted to monitor indoor environmental conditions in an educational building. A questionnaire was distributed during the monitoring period in order to understand the satisfaction level of occupants as well as their behavior preference. The results are utilized to model occupant behavior where fuzzy logic is preferred to tackle the uncertainty in the model parameters. Results denote that there is a significant potential of utilizing fuzzy logic to model occupant behavior under uncertain conditions similar to the real life.Öğe OntoH2G: A semantic model to represent building infrastructure and occupant interactions(Springer Science and Business Media Deutschland GmbH, 2019) Chbeir R.; Cardinale Y.; Corchero A.; Bourreau P.; Salameh K.; Charbel N.; Kallab L.; Angsuchotmetee C.; Calis G.In order to reduce the energy gap originated by the difference between existing tools estimations and real energy consumption, HIT2GAP European H2020 project aims at advancing on building control tools by providing a newer decision-making technology. Technically, HIT2GAP offers a platform inspired by previous reference architectures (e.g., Haystack) and complements them through a knowledge-based model, called OntoH2G, to store building information under a common vocabulary and consequently to enable fine-grained vision of the building with its equipment and occupants. OntoH2G advances over existing models on two main aspects: (i) being compliant with well-known ontologies in different domains in order to cover all energy building concepts, and (ii) its ability to represent user/occupant behavior, preferences, and interactions. In this paper, we present the main features of OntoH2G and describe how the well-known ontologies have been aligned in OntoH2G. © Springer Nature Switzerland AG 2019.Öğe Thermal comfort and occupant satisfaction of a mosque in a hot and humid climate(American Society of Civil Engineers (ASCE), 2015) Calis G.; Alt B.; Kuru M.Mosques are distinguished from other types of buildings by having an intermittent operation schedule. They are partially or fully occupied five times a day and the maximum occupancy is expected to occur on Friday prayers. As buildings with intermittent occupancy may not perform the same thermally as typical commercial and residential facilities, thermal comfort conditions and perception of occupants have to be investigated. This paper presents the results of a study monitoring indoor environmental conditions of a mosque in order to assess thermal comfort conditions. A historic mosque, which is located in a hot and humid climatic region of Turkey, was selected as a test building and thermal comfort conditions were monitored during two Friday prayers in August and September. Indoor air temperature, relative humidity and air velocity were collected via data loggers. The predicted mean vote (PMV) and predicted percentage of dissatisfied (PPD) indices were calculated and evaluated using the ASHRAE 55-2010 standard. In addition to this, a questionnaire based on Fanger's seven-point scale was conducted to understand the thermal sensation and preference of occupants. A comparison is provided to highlight the difference between the calculated and perceived satisfaction of occupants. © 2015 ASCE.Öğe Understanding the Relationship between Indoor Environmental Parameters and Thermal Sensation of users Via Statistical Analysis(Elsevier Ltd, 2017) Kuru M.; Calis G.Thermal comfort in indoor environments has a significant effect on user's health and wellbeing. Its effect becomes crucial especially in classrooms since it affects students' performance with respect to attention, comprehension and learning levels. This study assesses thermal comfort conditions via field measurements and subjective surveys. A university building, which is located in the Mediterranean climatic region of Turkey, was selected as a test site and the study was performed for ten days in the heating season. Indoor air temperature, mean radiant temperature, relative humidity and air velocity were monitored to obtain the Predicted Mean Vote (PMV) whereas a total of 235 subjective surveys were conducted to obtain the Actual Mean Vote (AMV). The comparison of PMV and AMV as well as the robustness of the relationship between PMV and AMV were analyzed via the t-test and Pearson correlation coefficient, respectively. In addition, the effect of users' relative humidity and air velocity perceptions on the thermal sensation and thermal acceptability were evaluated via cross tabulation and chi-square independence tests. The results show that the difference between the PMV and AMV values is statistically significant and the relationship between PMV and AMV has a very strong positive correlation. The results of the chi-square tests indicated that the thermal sensation and thermal acceptability are depended on users' relative humidity and air velocity perceptions. © 2017 The Authors.
