Training data

This paper develops an Artificial Neural Network (ANN) model based on 96 experimental data to forecast the dynamic modulus of asphalt concrete mixtures. This study applied the repeated KFold cross-validation technique with 10 folds on the training data set to make the simulation results more reliable and find a model with more general predictive power.

9p viengfa 28-10-2024 5 2   Download

In this paper, a Convolutional Neural Network (CNN) method is employed to classify the crack/noncrack aerial images captured on the surface of concrete structures. The CNN model was trained and validated using the available experimental data of 4000 previously published images.

4p vibecca 01-10-2024 1 1   Download

This study applies the GRU (Gated Recurrent Unit) model when selecting different values of batch-size, namely 16, 32, and 64, with varying epochs of 20, 50, 100, 150, and 200. The input data comprises observations collected by two GNSS CORS stations from the VNGEONET network, namely HYEN and CTHO, spanning from August 10, 2019, to March 18, 2022.

10p vibecca 01-10-2024 3 1   Download

This study aimed to analyze the current situation of vocational training for farmers and farmers’ needs for vocational training in the next years in extremely isolated communities. The primary data were collected from 480 farmers in 16 communes.

13p vibecca 01-10-2024 3 1   Download

In this paper, we propose an enhanced method (named FeaWAD*) that improves the data encoding strategy based on the FeaWAD network. These models require only a small fraction of anomalies for training.

9p viyoko 01-10-2024 7 1   Download

In this study, a supervised learning ANFIS model was developed to predict the compressive strength of concrete at 28 days. Data used in training and testing model were collected from a previous study.

13p vifilm 24-09-2024 5 1   Download

This paper describes a method to predict the fire resistance ratings of the wooden floor assemblies using Artificial Neural Networks. Experimental data collected from the previously published reports were used to train, validate, and test the proposed ANN model.

12p vifilm 24-09-2024 1 1   Download

n this work, the main aim is to map the potential zones of groundwater in Central Highlands (Vietnam) using a novel ensemble machine learning model, namely CG-LMT, which is a combination of two advanced techniques, namely Cascade Generalization (CG) and Logistics Model Trees (LMT). For this, a total of 501 wells data and a set of twelve affecting factors were gathered and selected to generate training and testing datasets used for building and validating the model.

10p dianmotminh02 03-05-2024 9 2   Download

This paper presents our approach that addresses the problem of transplanting a source speaker’s emotional expression to a target speaker, one of the Vietnamese Language and Speech Processsing (VLSP) 2022 TTS tasks. Our approach includes a complete data preprocessing pipeline and two training algorithms.

11p dianmotminh02 03-05-2024 8 3   Download

This study explores the use of teacher reflective practice, teacher networking and teacher collaboration, beyond formal ICT training, through blog-based professional development of English teachers in the Mumbai region of India. Using data collected from 32 teachers in three private schools of Mumbai, through ICT interactive workshop observations, questionnaires, interviews and blog comments, the case study explains whether and why blogging, as a learning community, has potential to add significant value to existing professional development of English teachers in Mumbai.

187p runthenight05 01-03-2023 10 3   Download

This changing external environment is the context for this 'practitioner research' investigative project - the development of a motorsports program as a case study of innovation and entrepreneurship at Wodonga Institute of TAFE. A participant-observer research approach was applied to examine the perceptions of the stakeholders about the development of the program. Data was collected through semi-formal interviews with stakeholders, maintaining a reflective research journal and reviewing related literature.

172p runthenight07 01-03-2023 7 3   Download

This paper focuses on exploring Machine learning methods to automate this process. The main challenge we face is in generating adequate training datasets to train the Machine learning model. Creating training data by manually segmenting real images is very labour-intensive, so we have instead tested methods of automatically creating synthetic training datasets which have the same attributes of the original images. The generated synthetic images are used to train a U-net Model, which is then used to segment the original bread dough images.

75p runordie3 06-07-2022 3 1   Download

Research objectives of the thesis: Research the theories of complex fuzzy sets, complex fuzzy logic and measures based on complex fuzzy sets; research and development of fuzzy inference system based on complex fuzzy sets; research applied techniques to reduce rules, optimize fuzzy rules in complex fuzzy inference system; research on how to represent rules based on fuzzy knowledge graphs to reduce inference computation time for the test set and deal with the cases where the new dataset is not present in the training data set.

27p beloveinhouse01 15-08-2021 16 4   Download

Since data representation is one of the factors that affect the training and testing time, a compact and complete detector generation algorithm is investigated; the thesis investigates optimal algorithms to generate detector set in AIS; they help to reduce both training time and detecting time of AIS-based IDSs.

103p larachdumlanat129 20-01-2021 18 4   Download

This paper proposes a new approach which combines different classifiers in order to make best use of each classifier. To build the new model, we evaluate the accuracy and performance (training and testing time) of three classification algorithms: ID3, Naitive Bayes and SVM.

8p tamynhan8 04-11-2020 13 3   Download

The research has a root intention, started from manager’s dilemma. In these near years, employee turnover rate is very high (from 20% - near 35% in per head office, branch offices). Expenditure for recruiting new employee is very high. After recruiting, newcomers need probationary process, they maybe pass or fail, even if newcomer fails, the company lost more expenditure for looking for other candidates, for training, etc.

87p donhuvy 14-09-2020 34 5   Download

Proposing a model to classify by fuzzy decision trees and a method to select the feature training samples set for classification process. Recommending the linguistic value treatment method of inhomogeneous attributes based on hedge algebra. Proposing the algorithms by fuzzy decision tree in order to be effective in predicting and simple for users.

26p gaocaolon6 30-07-2020 32 3   Download

The data show that, although the core group is highly qualified, it lacks staff with deep expertise in policy and climate change. As for the complementary group, the city has not focused on training it in both short and long terms. In order to improve the effectiveness of climate change response in the coming years.

8p capheny 28-02-2020 17 2   Download

The thesis only studies the situation of developing the financial resources for public higher education in Vietnam. The author performs statistics and summarizes the data on the structure of financial institutions at 55 institutions of higher education nationwide in all the training groups belonging to two groups of higher education institutions: The group is completely self-financed in terms of finance and group partially financial autonomy and carry out opinion surveys of students of 5 typical public tertialry institutions in 5 typical industry groups.

27p dungmaithuy 18-09-2019 47 4   Download

This paper proposes a procedural pipeline for wind forecasting based on clustering and regression. First, the data are clustered into groups sharing similar dynamic properties. Then, data in the same cluster are used to train the neural network that predicts wind speed. For clustering, a hidden Markov model (HMM) and the modified Bayesian information criteria (BIC) are incorporated in a new method of clustering time series data.

16p dieutringuyen 07-06-2017 37 2   Download