Architecture / Mimarlık

Permanent URI for this collectionhttps://hdl.handle.net/11147/24

Browse

Filters

1999 - 199912000 - 20096

Settings

End date: 2009Scopus Q: search.filters.scopusQuartile.Q1

Search Results

Now showing 1 - 7 of 7
  • Editorial
    How Doorknob Gets Its Meaning
    (Routledge, 2005) Doğan, Fehmi; Nersessian, Nancy J.
    Jerry Fodor’s (1998) Concepts: Where Cognitive Science Went Wrong (hereafter referred to as Concepts) and Geoffrey C. Bowker and Susan Leigh Star’s (1999) Sorting Things Out: Classification and its Consequences (hereafter referred to as Sorting) represent orthogonal views of concepts and categories stemming from two very different philosophical traditions. Fodor focuses on theories of concepts, whereas Bowker and Star discuss what categories and classification systems are. For Fodor, concepts are mental particulars that apply to things in the world (p. 23).
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    The Impact of Planimetric Configuration on Structurally Damaged Residential Buildings
    (Taylor and Francis Ltd., 2009) Kazanasmaz, Zehra Tuğçe
    This study was conducted to determine a significant relationship between planimetric configuration and vulnerability of hazardous buildings located in seismic zones by developing design and construction efficiency indicators. Case study examples were chosen from residential buildings in Bolu, Düzce and Kaynasli in Turkey, which were damaged by the 1999 earthquakes. Utilizing field survey drawings, efficiency quotients; compactness quotients; construction efficiency ratios; aspect ratios and height-to-base ratios were defined as planimetric configuration indicators. The significant relationship between these aspects and the damage level of buildings were determined through statistical analyses and scatter charts. Planimetric configuration - including building geometry, cantilever projections and layout of columns -was reviewed according to the Turkish Earthquake Code. Findings revealed certain dependencies for efficiency ratios, which would satisfactorily predict the seismic vulnerability of buildings based on planimetric configuration. Researchers in the field of architecture who are engaged in earthquake-resistant design may use the general methodology. In addition, architects and structural engineers can use this approach presented here to evaluate their design.
  • Article
    Citation - WoS: 91
    Citation - Scopus: 122
    Artificial Neural Networks To Predict Daylight Illuminance in Office Buildings
    (Elsevier Ltd., 2009) Kazanasmaz, Zehra Tuğçe; Günaydın, Hüsnü Murat; Binol, Selcen
    A prediction model was developed to determine daylight illuminance for the office buildings by using artificial neural networks (ANNs). Illuminance data were collected for 3 months by applying a field measuring method. Utilizing weather data from the local weather station and building parameters from the architectural drawings, a three-layer ANN model of feed-forward type (with one output node) was constructed. Two variables for time (date, hour), 5 weather determinants (outdoor temperature, solar radiation, humidity, UV index and UV dose) and 6 building parameters (distance to windows, number of windows, orientation of rooms, floor identification, room dimensions and point identification) were considered as input variables. Illuminance was used as the output variable. In ANN modeling, the data were divided into two groups; the first 80 of these data sets were used for training and the remaining 20 for testing. Microsoft Excel Solver used simplex optimization method for the optimal weights. The model's performance was then measured by using the illuminance percentage error. As the prediction power of the model was almost 98%, predicted data had close matches with the measured data. The prediction results were successful within the sample measurements. The model was then subjected to sensitivity analysis to determine the relationship between the input and output variables. NeuroSolutions Software by NeuroDimensions Inc., was adopted for this application. Researchers and designers will benefit from this model in daylighting performance assessment of buildings by making predictions and comparisons and in the daylighting design process by determining illuminance.
  • Article
    Citation - WoS: 66
    Citation - Scopus: 76
    Using Decision Trees for Determining Attribute Weights in a Case-Based Model of Early Cost Prediction
    (American Society of Civil Engineers (ASCE), 2008) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
    This paper compares the performance of three different decision-tree-based methods of assigning attribute weights to be used in a case-based reasoning (CBR) prediction model. The generation of the attribute weights is performed by considering the presence, absence, and the positions of the attributes in the decision tree. This process and the development of the CBR simulation model are described in the paper. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of residential building projects. The CBR results indicate that the attribute weights generated by taking into account the information gain of all the attributes performed better than the attribute weights generated by considering only the appearance of attributes in the tree. The study is of benefit primarily to researchers, as it compares the impact of attribute weights generated by three different methods and, hence, highlights the fact that the prediction rate of models such as CBR largely depends on the data associated with the parameters used in the model.
  • Article
    Citation - WoS: 87
    Citation - Scopus: 100
    Determining Attribute Weights in a Cbr Model for Early Cost Prediction of Structural Systems
    (American Society of Civil Engineers (ASCE), 2006) Doğan, Sevgi Zeynep; Arditi, David; Günaydın, Hüsnü Murat
    This paper compares the performance of three optimization techniques, namely feature counting, gradient descent, and genetic algorithms (GA) in generating attribute weights that were used in a spreadsheet-based case based reasoning (CBR) prediction model. The generation of the attribute weights by using the three optimization techniques and the development of the procedure used in the CBR model are described in this paper in detail. The model was tested by using data pertaining to the early design parameters and unit cost of the structural system of 29 residential building projects. The results indicated that GA-augmented CBR performed better than CBR used in association with the other two optimization techniques. The study is of benefit primarily to researchers as it compares the impact attribute weights generated by three different optimization techniques on the performance of a CBR prediction tool.
  • Article
    Citation - Scopus: 250
    A Neural Network Approach for Early Cost Estimation of Structural Systems of Buildings
    (Elsevier Ltd., 2004) Günaydın, Hüsnü Murat; Doğan, Sevgi Zeynep
    The importance of decision making in cost estimation for building design processes points to a need for an estimation tool for both designers and project managers. This paper investigates the utility of neural network methodology to overcome cost estimation problems in early phases of building design processes. Cost and design data from thirty projects were used for training and testing our neural network methodology with eight design parameters utilized in estimating the square meter cost of reinforced concrete structural systems of 4-8 storey residential buildings in Turkey, an average cost estimation accuracy of 93% was achieved.
  • Article
    Citation - WoS: 36
    Citation - Scopus: 47
    Perceptions of Process Quality in Building Projects
    (American Society of Civil Engineers (ASCE), 1999) Arditi, David; Günaydın, Hüsnü Murat
    A Delphi process and a questionnaire survey are conducted to investigate the differences in the perceptions of entry-level professionals and long-time practitioners with regard to process quality in building projects. The factors that affect process quality in the three phases (design, construction, and operation) of a building project's life cycle are identified and ranked by the respondents' perceived degree of importance. The findings indicate that the perceptions of entry-level professionals and long-time practitioners are in agreement for most (74%) of the factors. Given the differences in the respondents' background, expectations, and experience, differences in perceptions are to be expected in the remaining 26% of the factors. Analyzing these differences helps in revising and improving existing training courses and academic programs. It is recommended that college programs include courses that treat the administrative aspects involved in the building project in great detail and that continuing education programs cover quality training and life cycle cost analysis.