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    Heuristic Strategies: Achieving Influence Motivation with Success to Design Industrial Products in Projects from the Department of Architectural Education and Design
    (2022-01-01)
    Egwutvongsa, Songwut
    ;
    Piramgran, Thanat
    ;
    Seviset, Somchai
    This research aimed to study the achievement of motivation from the learning procedure of heuristic strategies. Besides, it resulted in the success of design product projects from the students in the Department of Architectural Education and Design, King Mongkut’s Institute of Technology Ladkrabang with the learning comparison method and student satisfaction between control groups for normal study and experiment groups with heuristic strategies. This research studied the results from fourth-year student groups studying in the curriculum of Architectural Education and Design. A total of forty-four people were selected by using the observation method and asking for satisfied attributions in the groups to represent the score levels from the personal project assessment. In this case, it also used a 5-point rating scale to make t-test data analysis for Independence with results comparison, and it was found that the experiment group studying with heuristic strategies had the testing scores of the personal project assessment in the higher level than the controlling group with studying in a normal way with statistical significance at the level of.05, including with the reliability assessment from the students in the designing product project, which found that the experiment group with studying for heuristic strategies gaining the reliability level from the personal project at a higher level than the controlling group with studying in a normal way with statistical significance at the level of.05.
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    A method to improve the accuracy of simulation models: A case study on photovoltaic system modelling
    (2021-01-02)
    Bupi, Aekkawat
    ;
    Kittisontirak, Songkiate
    ;
    Chinnavornrungsee, Perawut
    ;
    Songtrai, Sasiwimon
    ;
    Manosukritkul, Phassapon
    This research presents a method to improve data accuracy for the more efficient data management of the studied applications. The data accuracy was improved using the preciseness function learning model (PFL model). It contains a database in which the amount of data is more or less dependent on all of the possible behavior of the studied application. The proposed model improves data with functions obtained by optimizing curves to represent the data at each point, which estimate the database’s diffusion behavior, and functions can be built around all of the various forms of databases. The proposed model always updates its database after processing. It has been learning to optimize the processing precision. In order to verify the precision of the proposed model through its application to a PV system simulation model, the process’s database should contain at least one year. This is because the overall behavior of the PV power output in Thailand depends on the seasonal weather; Thailand has three seasons in a period of one year. The testing was performed by comparing the PV power output. The simulation results with the actual measurement data (12 MW PV system) can be divided into two conditions: the daily comparison and the seasonal PV power output. As a result, the proposed model can accurately simulate the PV power output despite the sudden daily climate change. The average nRMSE (normalized RMSE) of the proposed model is very low (1.23%), and ranges from 0.30% to 2.26%. Therefore, it has been proven that this model is very accurate.
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    Information Engineering Course Management in Faculty of Engineering, KMITL towards excellence
    (2021-01-01)
    Purahong, Punyaruethai
    ;
    Archevapanich, Tuanjai
    ;
    Chaowalittawin, Vasutorn
    ;
    Punthang, Donnaporn
    ;
    Millerteacher, Gregory P.
    This article represents the management of Information Engineering course in faculty of Engineering, KMITL towards excellence. Sample group is the parental units of who registered since 2017 until 2020 for 15 people, by purposive sampling. The researcher later presenting the Information Engineering course management. Then make a parental satisfaction assessment form about the Information Engineering course management in faculty of Engineering, King Mongkut's Institute of Technology Ladkrabang, towards excellence of 7 subject. The conclude of assessment says that the parental units are having a good level of satisfaction and the arithmetic mean is 4.72 and the standard deviation is 0.56 (\overline{X} =4.27, S.D. = 0.56)