Machine learning methods

This article conducts an exhaustive investigation into the utilization of machine learning (ML) methods for forecasting the maximum load capacity (MLC) of circular reinforced concrete columns (CRCC) using Fiber-Reinforced Polymer (FRP). Extreme Gradient Boosting (XGB) algorithm is combined with novel metaheuristic algorithms, namely Sailfish Optimizer and Aquila Optimizer, to fine-tune its hyperparameters.

18p viengfa 28-10-2024 1 1   Download

The results of using machine learning via genetic programming (GP) to automatically generate novel effective length factor formula in accordance with AISC standard are presented in this article. The data points obtained from applying the numerical method equation solving for the transcendental equation for the effective length of the braced frame were fed into the machine learning algorithm.

5p vibecca 01-10-2024 3 1   Download

This paper presents a novel for Doppler frequency compensation in highspeed railway communication based on the results of estimating the train's velocity using machine learning algorithms. By leveraging advanced algorithm such as neural networks, our method dynamically predicts and compensates for Doppler shifts in real-time.

15p vibecca 01-10-2024 2 1   Download

This paper is aimed at evaluating the efficiency of Vietnamese SMS spam detection methods on different variants of Vietnamese datasets by utilizing both traditional machine learning models and deep learning models.

8p viyoko 01-10-2024 2 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

Currently, machine learning not only solves simple problems such as object classification but also machine learning is widely applied in the field of computer vision such as identification systems, object detection, and modules in the authentication system, intelligent processing algorithms such as automatic driving, chatbot, etc.

14p viyoko 01-10-2024 1 1   Download

Output-only methods based on machine/deep-learning algorithms are highly practical approaches for timely detecting potential damages in civil structures as they directly employ measured vibration signals but do not require exact knowledge of input loading nor the service interruption for manual inspection.

14p vifaye 20-09-2024 1 1   Download

One of the limitations of the BDI (Belief-Desire-Intention) model is the lack of any explicit mechanisms within the architecture to be able to learn. In particular, BDI agents do not possess the ability to adapt based on past experience. This is important in dynamic environments as they can change, causing previously successful methods for achieving goals to become inefficient or ineffective.

108p runthenight07 01-03-2023 10 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

Alternative polyadenylation (APA) affects most mammalian genes. The genome-wide investigation of APA has been hampered by an inability to reliably profile it using conventional RNA-seq. We describe ‘Quantification of APA’ (QAPA), a method that infers APA from conventional RNA-seq data.

18p vimichaelfaraday 25-03-2022 17 1   Download

The rapid growth in number, sophistication, and diversity of Android malware poses a great difficulty in extracting and analyzing features and behaviors. The traditional approach, which using only API calls and permissions to extract features, has no longer yielded meaningful results.

12p tamynhan5 10-12-2020 9 2   Download

We present machine learning models for fast estimating atomic forces and energies. In our method, the total energy of a system is approximated as the summation of atomic energy which is the interaction energy with its surrounding chemical environment within a certain cutoff radius.

7p tamynhan6 14-09-2020 16 1   Download

In this paper, we propose a mechanism to optimize range of EV by integrating some of the best methods to estimate rotor position, efficient temperature control modules and machine learning algorithms that analyze the vehicle’s environment and driving pattern.

10p lucastanguyen 01-06-2020 19 1   Download

The resulting model is a Document Retriever, called QASA, which is then integrated with a machine reader to form a complete open-domain QA system. Our system is thoroughly evaluated using QUASAR-T dataset and shows surpassing results compared to other state-of-the-art methods.

67p tamynhan1 13-06-2020 21 4   Download

This article implements a face detection process as a preliminary step to monitor the state of drowsiness on vehicle's drivers. We propose an algorithm for pre-detection based on image processing and machine learning methods. A Gabor filter bank is used for facial features extraction.

4p cathydoll5 27-02-2019 31 0   Download

In the paper, we are going to present a spam email filtering method based on machine learning, namely Naïve Bayes classification method because this approach is highly effective. With the learning ability (self improving performance), a system applied this method can automatically learn and ameliorate the effect of spam email classification. Simultaneously, the ability of system’s classification is also updated by new incoming emails, therefore, it is very difficult for spammers to overcome the classifier, compared to traditional solutions.

5p vision1234 21-06-2018 23 3   Download

Phishing is a real threat on the Internet nowadays. Therefore, fighting against phishing attacks is of great importance. In this paper, we propose a solution to this problem by applying Genetic Programming with features selection methods to phishing detection problem. We conducted the experiments on a data set including both phishing and legitimate sites collected from the Internet. We compared the performance of Genetic Programming with a number of other machine learning techniques and the results showed that Genetic Programming produced the best solutions to phishing detection problem.

6p blackwidow123 15-06-2018 25 1   Download

When computer virus wide spreads in the world nowadays, anti-virus needs to improve their identifying methods to enhance the performance. In this paper, we introduce a new method to diagnose computer virus. First, we analyse the characteristics of viral data type to define virus classes through object-oriented methods. Second, we study the machine learnning mechanism for each virus class. Finally, we apply these learning forms to a data processing stage of a machine learning anti-virus expert system.

10p binhminhmuatrenngondoithonggio 09-06-2017 67 5   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

(BQ) The study sheds light on the powerful learning capability of ANFIS models and its superiority over the conventional polynomial models in terms of modelling complex non-linear machining processes

15p xuanphuongdhts 27-03-2017 41 2   Download