Retracted: Highway Traffic Flow Prediction Algorithm Based on Multiscale Transformation and Convolutional Networks by Journal of Control Science and Engineering

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Visualization of large-scale user association feature data based on a nonlinear dimensionality reduction method by Nong Linlin

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Scheduling of home energy management systems for price-based demand response and end-users discomfort reduction by Kamyab Gholam-Reza

“…This optimization problem is solved using a simulated annealing algorithm across various scenarios with different maximum allowable values for the discomfort index. …”
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An algorithm to assess importance of predictors in systematic reviews of prediction models: a case study with simulations by Ruohua Yan, Chen Wang, Chao Zhang, Xiaohang Liu, Dong Zhang, Xiaoxia Peng

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Prediction of Telkomsel 4G LTE Card Sales using The K-Nearest Neighbor Algorithm by Alfiana Fontes Martins, Yasinta Oktaviana Legu Rema, Debora Chrisinta, Alejandro Jr. V. Matute, Krisantus Jumarto Tey Seran

“…This study aims to develop a precise model for predicting card sales using the K-Nearest Neighbor (KNN) algorithm and to offer recommendations for improving prediction quality by addressing issues related to data imbalance and overfitting. …”
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A recommender algorithm based on SVD ++model under trust network by Peiwu CHEN, Fangxing SHU

Subjects: “…recommender algorithm;latent factor model;trust network;rating prediction…”
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Cooling Load Prediction via Support Vector Regression in Individual and Hybrid Approaches by Honglei Yao, Andrew Topper

“…Moreover, the hybrid SVCS model, with its minimal RMSE value of 0.747 and remarkable R2 value of 0.994, consistently yields reliable results for CL prediction. This study advances the field of energy-efficient building management by demonstrating how machine learning methods and clever optimization algorithms can be used to predict cooling loads accurately.…”
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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…Objectives: The existing linear prediction (LP) formant estimation algorithms are difficult to locate formant precisely because of the pseudo root interference and interaction between poles.Because of the low order fitting formant of LP prediction,the accuracy of formant extraction is fundamentally limited.It is difficult to remove false roots and spectrum aliasing caused by pole interaction in the formant extraction of high-order LP.In order to solve the problem of large error of LP formant detection,a formant estimation algorithm based on high-order LP coefficient root value screening was proposed. …”
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AQSA—Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices by Ana Belén Peñaherrera-Pazmiño, Ramiro Fernando Isa-Jara, Elsa Hincapié-Arias, Silvia Gómez, Denise Belgorosky, Eduardo Imanol Agüero, Matías Tellado, Ana María Eiján, Betiana Lerner, Maximiliano Pérez

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Improved K-means clustering and adaptive distance threshold for energy reduction in WSN-IoTs by Azamuddin Ab Rahman, Sakib Iqram Hamim

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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

“…Among these algorithms, the Two-Class Boosted Decision Tree method demonstrated outstanding prediction ability, achieving a 100% accuracy rating. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

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Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

“…This study leverages the UCI heart disease dataset to assess the effectiveness of various Machine Learning models in predicting heart diseases. This paper proposed an advanced prediction method that combines feature selection using a hybrid of Genetic Algorithm (GA) and Cuckoo Search Optimization (CSO) with a majority voting ensemble of Convolutional Neural Network and Random Forest. …”
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Noise Reduction of Steam Trap Based on SSA-VMD Improved Wavelet Threshold Function by Shuxun Li, Qian Zhao, Jinwei Liu, Xuedong Zhang, Jianjun Hou

“…Therefore, to minimize the impact of environmental noise on valve internal leakage identification, it is necessary to preprocess the original acoustic emission signals through noise reduction before identification. To address the above problems, a denoising method based on a sparrow search algorithm, variational modal decomposition, and improved wavelet thresholding is proposed. …”
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The Development Path and Carbon-Reduction Method of Low-Carbon Pilot Urban Areas in China by Lining Zhou, Qingqin Wang, Haizhu Zhou, Yiqiang Jiang, Rongxin Yin, Tong Lu

“…At the same time, after comparing models, such as random forest and support vector machine, the XGBoost algorithm is adopted for short-term prediction (R² = 0.984, MAE = 0.195). …”
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Improving appendix cancer prediction with SHAP-based feature engineering for machine learning models: a prediction study by Ji Yoon Kim

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Validation of three models (Tolcher, Levine, and Burke) for predicting term cesarean section in Chinese population by Fangcan Sun, Minhong Shen, Bing Han, Youguo Chen, Fangfang Wu

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Application of genetic algorithmbin an active noise control system by Grzegorz MAKAREWICZ

Subjects: “…genetic algorithm…”
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Heuristic Global Optimization for Thermal Model Reduction and Correlation in Aerospace Applications by João P. Castanheira, Beltran N. Arribas, Rui Melicio, Paulo Gordo, André R. R. Silva

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Reversible data hiding algorithm based on asymmetric histogram shifting by Yufen HE, Zhaoxia YIN, Jin TANG, Lei LIU, Shilei HUANG

“…The shifting of two asymmetric histograms in opposite directions in data embedding respectively had produced the pixel compensation and restore effect,a better reversible data hiding algorithm based on pixel prediction was proposed,two asymmetric histograms of prediction error were generated on the more right and the more left side of zero value,when they were shifed in the second data embedding stage,more pixels would be restored to the original image pixel value to reduce image distortion and improve the image quality.Compared with the traditional algorithm,it reduces the amount of pixels involved in the histogram shifting and protects the quality of secret image.…”
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