CANKIRI KARATEKIN UNIVERSITY Bologna Information System


  • Course Information
  • Course Title Code Semester Laboratory+Practice (Hour) Pool Type ECTS
    Modeling of Forest Road Networks with Artificial Neural Networks OR1523 FALL-SPRING 3+0 E 6
  • ECTS / WORKLOAD
  • ActivityPercentage

    (100)

    NumberTime (Hours)Total Workload (hours)
    Course Duration (Weeks x Course Hours)14342
    Classroom study (Pre-study, practice)14228
    Assignments1512525
    Short-Term Exams (exam + preparation) 0000
    Midterm exams (exam + preparation)3513535
    Project0000
    Laboratory 0000
    Final exam (exam + preparation) 5013535
    Other 0000
    Total Workload (hours)   165
    Total Workload (hours) / 30 (s)     5,5 ---- (6)
    ECTS Credit   6
  • Course Content
  • Week Topics Study Metarials
    1 Definitions and concepts related to forest road networks Reading the chapter titled Unit 1 in the course note prepared using a textbook and ancillary document
    2 Definitions and concepts related to forest road networks Reading the chapter titled Unit 1 in the course note prepared using a textbook and ancillary document
    3 Factors affecting the planning of forest road networks Reading the chapter titled Unit 2 in the course note prepared using a textbook and ancillary document
    4 Planning stages of forest road networks Reading the chapter titled Unit 2 in the course note prepared using a textbook and ancillary document
    5 Factors affecting alternative route detection Reading the chapter titled Unit 3 in the course note prepared using a textbook and ancillary document
    6 Alternative route detection Reading the chapter titled Unit 3 in the course note prepared using a textbook and ancillary document
    7 Approaches used to decide on optimum alternatives Reading the chapter titled Unit 4 in the course note prepared using a textbook and ancillary document
    8 Artificial Neural Networks and Fuzzy Logic approaches, related definitions and concepts Reading the chapter titled Unit 4 in the course note prepared using a textbook and ancillary document
    9 Basic principles in Artificial Neural Networks and Fuzzy Logic approach Reading the chapter titled Unit 5 in the course note prepared using a textbook and ancillary document
    10 Software used in Artificial Neural Networks and Fuzzy Logic approach Reading the chapter titled Unit 5 in the course note prepared using a textbook and ancillary document
    11 Data normalization methods and entering data into software environment in Artificial Neural Networks and Fuzzy Logic approaches Reading the chapter titled Unit 6 in the course note prepared using a textbook and ancillary document
    12 Entering criteria in Artificial Neural Networks and Fuzzy Logic software environment and determining functions before analysis Reading the chapter titled Unit 6 in the course note prepared using a textbook and ancillary document
    13 Conducting the analysis, interpreting the results by evaluating the multi-criteria analysis outputs Reading the chapter titled Unit 7 in the course note prepared using a textbook and ancillary document
    14 Calculation of model prediction successes by making accuracy analysis of the obtained models Reading the chapter titled Unit 7 in the course note prepared using a textbook and ancillary document
    Prerequisites -
    Language of Instruction Turkish
    Responsible Assoc. Prof. Dr. Ender BUĞDAY
    Instructors -
    Assistants -
    Resources 1- ERDAŞ, O. (1997), Orman Yolları (Cilt: I, II), K.T.Ü. Orman Fakültesi Yayınları, Trabzon. 2- Schalkoff, R. J. (1997). Artificial neural networks (Vol. 1). New York: McGraw-Hill. 3- Bugday, E. (2018), Application of Artificial Neural Network System Based on ANFIS Using GIS for Predicting Forest Road Network Suitability Mapping. Fresenius Environmental Bulletin, Volume 27 ? No. 3/2018 pages 1656-1668.
    Supplementary Book -
    Goals To introduce the use and results of new and current approaches in the planning of forest road networks, to explain Artificial Neural Networks and Fuzzy Logic approaches in modeling.
    Content It is to obtain fast and reliable prediction models based on multiple factors in optimal forest road network planning and exposing spatial distribution.
  • Program Learning Outcomes
  • Program Learning Outcomes Level of Contribution
    1 Must learn the methods of both improving the basic sciences and engineering knowledge and obtaining new knowledges at a level of expertise 4
    2 Must be able to design, develop, and apply methods and experiments at advanced level to solve forestry problems, and analyses and interpret their results 4
    3 Must be able to provide solutions for the country?s forestry and environmental problems by considering global, public and ecosystem conditions -
    4 Must be able to setup interdisciplinary approach to reach an advanced solution for forestry problems 4
    5 Must be able to act in an advanced level of professional ethics and responsibility during the identification and resolution of problems encountered in forestry -
    6 Must be able to do the task in a single or multi-disciplinary working groups, and be able to show effective communication -
    7 Must have the ability to effective use of both information technologies and a foreign language at an advanced level 4
    8 Must be able to describe, foresee and solve the current problems in the fields of forestry and other related problems at advanced level brought by current global developments -
    9 Must be able to use the tools and techniques required for forestry applications at an advanced level -
    10 Must be able to think, interpret, analyse and synthesize forestry practices at an advanced level by using a three dimensional perspective 4
    11 Must be able to research and survey any kinds of natural resources and event, and write advanced reliable reports by using the achieved findings -
    12 Must be able to understand the necessity of life-long learning at an advanced level, and to be able to use the methods that keeps obtained knowledge up date -
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