Evaluation of Machine Learning and Ensemble Learning Models for Classification Using Delivery Data by İrem Karakaya

Subjects: Get full text

Dual Convolution Neural Networks of Ensemble Learning with Attention Mechanism for Rice Classification by Cheng Linfeng

“…The aim of this project is to develop a dual convolutional neural network for ensemble learning based on the initial model and the res network model, and apply the ensemble model to the rice classification problem. …”
Get full text

An Evapotranspiration Assimilation Method Based on Ensemble Kalman Filter and À Trous Wavelet by Shaohui Chen, Jianwei Qi, Xiaomin Sun, Xiangzheng Deng, Jing Tian

“…In this paper, a perturbed ensemble Kalman filter (PEKF) and à trous wavelet transform (AWT) integrated method are proposed to implement the evapotranspiration assimilation. …”
Get full text

Customer Churn Modeling via the Grey Wolf Optimizer and Ensemble Neural Networks by Maryam Rahmaty, Amir Daneshvar, Fariba Salahi, Maryam Ebrahimi, Adel Pourghader Chobar

Get full text

Discriminating neural ensemble patterns through dendritic computations in randomly connected feedforward networks by Bhanu Priya Somashekar, Upinder Singh Bhalla

Subjects: Get full text

Conv‐ELSTM: An ensemble deep learning approach for predicting short‐term wind power by Guibin Wang, Xinlong Huang, Yiqun Li, Hong Wang, Xian Zhang, Jing Qiu

“…This article introduces a hybrid data‐driven framework that employs an ensemble deep learning model to provide highly precise short‐term wind power predictions. …”
Get full text

An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features by Junjie Wang, Lei Jiang, Le Zhang, Yaqi Liu, Qihong Yu, Yuheng Bu

Subjects: Get full text

Diabetes Risk Assessment: A Comparative Study of Decision Trees and Ensemble Learning Models by Lei Tianxing

“…This process ensures that all possible combinations of indicators are mapped to a single classification result. Ensemble Learning, on the other hand, leverages multiple classifiers with assigned weights to form a robust ensemble. …”
Get full text

Solar GHI Ensemble Prediction Based on a Meteorological Model and Method Kalman Filter by Yuanyuan Liu

“…As the accuracy of the version output related to its specific position is often questionable, group prediction constituting three members is suggested and agreed upon measurement. Also, this ensemble prediction provides an estimation of the solar global horizontal irradiance uncertainty (i.e., coverage rate of the prediction interval), which can be useful to provide flexible energy production forecasts. …”
Get full text

Func-Bagging: An Ensemble Learning Strategy for Improving the Performance of Heterogeneous Anomaly Detection Models by Ruinan Qiu, Yongfeng Yin, Qingran Su, Tianyi Guan

Subjects: “…ensemble learning…”
Get full text

Application of an Improved Ensemble Local Mean Decomposition Method for Gearbox Composite Fault Diagnosis by Zhijian Wang, Junyuan Wang, Wenan Cai, Jie Zhou, Wenhua Du, Jingtai Wang, Gaofeng He, Huihui He

“…Compared with LMD, ELMD, CELMD, and CELMDAN, it shows that improved ensemble local mean decomposition method is an effective method for extracting composite fault features.…”
Get full text

Solar photovoltaic panel cells defects classification using deep learning ensemble methods by H. Tella, A. Hussein, S. Rehman, B. Liu, A. Balghonaim, M. Mohandes

Subjects: Get full text

Blood Vessel Segmentation and Classification of Diabetic Retinopathy with Machine Learning-Based Ensemble Model by Cihan Akyel, Bünyamin Ciylan

Subjects: Get full text

Fault Frequency Identification of Rolling Bearing Using Reinforced Ensemble Local Mean Decomposition by Bo Qin, Quanyi Luo, Juanjuan Zhang, Zixian Li, Yan Qin

“…To overcome this problem, we propose a reinforced ensemble local mean decomposition method to capture and screen the essential faulty frequencies of rolling bearing, further boosting fault diagnosis accuracy. …”
Get full text

Rapid Detection of Hybrid Maize Parental Lines Using Stacking Ensemble Machine Learning by M. Aqil, M. Azrai, M. J. Mejaya, N. A. Subekti, F. Tabri, N. N. Andayani, Rahma Wati, S. Panikkai, S. Suwardi, Z. Bunyamin, E. Roy, M. Muslimin, M. Yasin, E. Prakasa

“…The research’s primary contribution is the integration of two widely used transfer learning architectures, Inception V3 and SqueezeNet, with stacking ensemble machine learning using four algorithms (logistic regression, support vector machine, random forest, and k-nearest neighbors) for rapid classification of tassel images. …”
Get full text

Automatic Rock Classification Algorithm Based on Ensemble Residual Network and Merged Region Extraction by Chenlu Guo, Zhiyuan Li

“…The effect of misclassification in certain regions on the results is eliminated by ensemble learning based on the voting method. The classification results are further improved. …”
Get full text

Novel Ensemble Approach with Incremental Information Level and Improved Evidence Theory for Attribute Reduction by Peng Yu, Yifeng Zheng, Ziwen Liu, Baoya Wei, Wenjie Zhang, Ziqiong Lin, Zhehan Li

“…To address the above problem, we propose an ensemble approach based on an incremental information level and improved evidence theory for attribute reduction (IILE). …”
Get full text

The Grand Ensemble of Orly-Choisy-le-Roi: the Construction, Deconstruction and Reconstruction of a Neighbourhood by Caterina Quaglio

Subjects: Get full text

The Measurement and Elimination of Mode Splitting: From the Perspective of the Partly Ensemble Empirical Mode Decomposition by Bin Liu, Peng Zheng, Qilin Dai, Zhongli Zhou

“…The problems of mode mixing, mode splitting, and pseudocomponents caused by intermittence or white noise signals during empirical mode decomposition (EMD) are difficult to resolve. The partly ensemble EMD (PEEMD) method is introduced first. The PEEMD method can eliminate mode mixing via the permutation entropy (PE) of the intrinsic mode functions (IMFs). …”
Get full text

Marker and source-marker reprogramming of Most Permissive Boolean networks and ensembles with BoNesis by Paulevé, Loïc

“…Finally, we lift the reprogramming problems to ensembles of BNs, as supported by BoNesis, bringing insight on possible and universal reprogramming strategies. …”
Get full text