000			01497nam a22001697a 4500
003			OSt
005			20250321110021.0
008			250321b |||||||| |||| 00| 0 eng d
040			_cNVSU
100			_aSegundo, Carlita G.
245			_aPrice prediction with bidirectional long short-term memory algorithm for high value commercial crops/ _cCarlita G. Segundo
300			_axi, 64 leaves : _bcolored illustrations ; _c28 cm.
500			_aThis paper modeled and predicted the price of High Value Commercial Crop using Bidirectional LSTM algorithm. Price of tomato and squash datasets plus software and hardware requirements were utilized in its development and Root Mean Squared Error, and loss computation was performed as assessment method. Gaining low Root Mean Squared Error and losses indicate accurate prediction capability of the system. The computed RMSE were 2.07 and 2.04 for tomato and squash respectively. Losses that started from 0.0553 and 0.0570 for training and test dataset respectively which both finish at 0.0128 for tomato; losses for squash started from 0.0172 and 0.0176 for training and test dataset respectively and finish at 0.0019 for training dataset and 0.0020 for test dataset. Price prediction capability of the system is useful to farmers, farm investors and government agencies as it guides them in decision making.
500			_aThesis (Master of Information Technology)
504			_aIncludes appendices and bibliographical references.
942			_2ddc _cTH _n0
999			_c282 _d282