Özet:

The architectural design process takes place with the collaboration of people specializing in many different topics, from the making of the main design decisions to the detailing phase, but the making of the main decisions, the planning organization, the mass fiction, etc. The basic decisions are made by the architect. Computer-Supported Design (CAD) programs are usually effective after the main design decisions are made. Therefore, the need to change the main decisions made in the process during the carrier system account becomes a frequent situation. In order to avoid this, in the early stages of architectural design, it is necessary to participate as a design entrance of the carrier system fiction with the consciousness of the earthquake architecture; for in the architectural design phase the carrier system fiction is not well considered, in the implementation project phase it is faced with unexpected revisions and therefore causes serious losses both in the process and in the cost.   The aim of this study is to create an Unregularity Control Assistant (DK Assistant) using deep learning and image processing methods to create a problem-solving way, in the early stages of the design, which can provide architects with general information about the conformity of the system decisions for transportation to earthquake regulations. Thus, the right decisions will be made in the early stages of design, and unexpected revisions that may occur in the stage of the implementation project will be prevented.

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