![](images/graphics/blank.gif)
Random forest model
-
A deep learning approach combining autoencoder with supervised classifiers for IoT anomaly detection
Anomaly detection for Internet of things (IoT) networks is a challenging issue due to the huge number of devices that connect to each other and generate huge amounts of data. In this study, we propose a model combining Autoencoder (AE) with classification algorithms to build an endto-end architecture for processing, feature extraction and data classification.
13p
viambani
18-06-2024
6
1
Download
-
Currently, R is showing its strengths and benefits in data analysis in general and forestry data in particular. R can perform new, difficult and complex statistical analyses such as linear mixed model, replicated point patter analysis, etc. In the forestry data analysis, checking independence between samples and random effects has not been done so far by scientists. This is a really difficult problem in forestry data analysis, because it is an important basis for choosing analytical tools later on.
10p
vilarry
01-04-2024
1
0
Download
-
The paper presents a study on the application of basic machine learning models for churn customer classification. Churn prediction is an essential task in customer retention for businesses, and accurate identification of customers who are likely to churn can significantly impact the organization's revenue and customer satisfaction.
7p
vibego
02-02-2024
4
1
Download
-
In this study, an advanced machine learning model based on artificial intelligence, the Random Forest, was developed and applied to predict the bearing capacity of piles. This model is used as a predefined model applied in the MonteCarlo simulation method to determine the reliability of the pile-bearing capacity.
13p
vijeff
27-11-2023
9
5
Download
-
Using texture features derived from contrast-enhanced computed tomography (CT) combined with general imaging features as well as clinical information to predict treatment response and survival in patients with hepatocellular carcinoma (HCC) who received transarterial chemoembolization (TACE) treatment.
12p
vischultz
20-10-2023
2
1
Download
-
The performance of the proposed RF model is evaluated using three statistical measurements: root mean squared error (RMSE), mean absolute error (MAE), and correlation coefficient (R). The results show that the RF model has high predictive accuracy with an RMSE of 210 cnt/h, an MAE of 121 cnt/h, and an R of 0.90. The performance of the RF model is also compared with a linear regression model and shows superior accuracy.
9p
visharma
20-10-2023
8
4
Download
-
Self-compacting concrete (SCC) is a construction material with many advantages, including high performance and the capacity to selfcompact without mechanical vibration. As a result, SCC is widely used in construction, especially at locations where concrete structures are difficult to construct. The study constructed the RF model using a dataset of 507 experimental results collected, which is the biggest data collection compared to previous studies on this subject.
12p
visharma
20-10-2023
10
6
Download
-
In this study, the Machine Learning (ML) approach has been adopted using Random Forest (RF) model to estimate the CBR of the soil based on 10 input parameters such as Plasticity Index (PI), Liquid Limit (LL), Silt Clay content (SC), Fine Sand content (FS), Coarse sand content (CS), Optimum Water Content (OWC), Organic content (O), Plastic Limit (PL), Gravel content (G), and Maximum Dry Density (MDD), which can be easily determined in the laboratory.
14p
visharma
20-10-2023
8
4
Download
-
This study aimed to evaluate the clinical significance of a novel systemic immune-inflammation score (SIIS) to predict oncological outcomes in upper urinary tract urothelial carcinoma(UTUC) after radical nephroureterectomy(RNU).
15p
visharma
20-10-2023
2
2
Download
-
In recent years, an increasing number of studies have revealed that patients’ preoperative inflammatory response, coagulation function, and nutritional status are all linked to the occurrence, development, angiogenesis, and metastasis of various malignant tumors.
13p
visharma
20-10-2023
5
2
Download
-
Colorectal cancer (CRC) is a heterogeneous disease, with subtypes that have different clinical behaviours and subsequent prognoses. There is a growing body of evidence suggesting that right-sided colorectal cancer (RCC) and left-sided colorectal cancer (LCC) also differ in treatment success and patient outcomes. Biomarkers that differentiate between RCC and LCC are not well-established.
11p
vioracle
29-09-2023
3
2
Download
-
Accurate prediction models for spatial prediction of forest fire danger play a vital role in predicting forest fires, which can help prevent and mitigate the detrimental effects of such disasters. This research aims to develop a new ensemble learning model, HHO-RSCDT, capable of accurately predicting spatial patterns of forest fire danger.
19p
viisac
15-09-2023
3
3
Download
-
In this article, an RF model is developed in predicting the slump and strength of concrete using mixed mineral admixtures from blast furnace slag and silicafume. The criterions to evaluate the accuracy of the models are the R squared (R2 ) and the root mean square error (RMSE).
13p
viengels
25-08-2023
10
3
Download
-
Suicide is one of the leading causes of death worldwide, yet clinicians find it difficult to reliably identify individuals at high risk for suicide. Algorithmic approaches for suicide risk detection have been developed in recent years, mostly based on data from electronic health records (EHRs). Significant room for improvement remains in the way these models take advantage of temporal information to improve predictions.
10p
vighostrider
25-05-2023
2
2
Download
-
Genome-wide association studies (GWAS) interrogate large-scale whole genome to characterize the complex genetic architecture for biomedical traits. When the number of SNPs dramatically increases to half million but the sample size is still limited to thousands, the traditional p-value based statistical approaches suffer from unprecedented limitations.
11p
vinarcissa
21-03-2023
5
1
Download
-
This article develops the algorithms, models and program to assess the technical risks in the period of construction and service of expressway bridges in Vietnam using Machine Learning, in order to solve the current limitations in this work.
13p
viargus
20-02-2023
1
1
Download
-
Identification of unknown fungal species aids to the conservation of fungal diversity. As many fungal species cannot be cultured, morphological identification of those species is almost impossible. But, DNA barcoding technique can be employed for identification of such species.
13p
vihagrid
30-01-2023
3
3
Download
-
Acceptance of new rice genotypes demanded by rice value chain depends on premium value of varieties that match consumer demands of regional preferences. High throughput prediction tools are not available to breeders to classify cooking and eating quality (CEQ) ideotypes and to capture texture of varieties.
12p
viginny
30-12-2022
7
2
Download
-
Structural elucidation of compounds detected with liquid chromatography coupled to high resolution mass spectrometry is a challenging and time-consuming step in the workflow of non-targeted analysis and often requires manual validation of the results. Retention time, alongside exact mass, isotope pattern, fragmentation spectra, and collision cross-section, is valuable information for ruling out unlikely structures and increasing the confidence in others.
12p
viginny
23-12-2022
6
2
Download
-
The paper proposes a novel method that applies Buckingham's Pi theory and the Random Forest regression to improve the prediction accuracy of the sequent depths of the hydraulic jump in the trapezoidal channel. The study has shown that Machine Learning models can be efficient for the determination of the geometrical features of the jump and have high ability in many real projects.
9p
vispyker
14-11-2022
13
4
Download
CHỦ ĐỀ BẠN MUỐN TÌM
![](images/graphics/blank.gif)