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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Effect of a health education program on reduction of pediculosis in school girls at Amphoe Muang, Khon Kaen Province, Thailand. by Manachai Yingklang, Chatchawan Sengthong, Ornuma Haonon, Rungtiwa Dangtakot, Porntip Pinlaor, Chulaporn Sota, Somchai Pinlaor

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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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KDDC: a new framework that integrates kmers, dataset filtering, dimension reduction and classification algorithms to achieve immune cell heterogeneity classification by Nan Zhang, Nan Zhang, Shishun Zhao, Runze Wu, Xizi Luo, Ming Yang, Zecheng Chang, Jianting Xu

“…IntroductionIntegrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various disease states.MethodsHere, we propose a novel KDDC framework that integrates kmers, dataset selection, dimensionality reduction and classification algorithms to facilitate the heterogeneous classification of immune cells.Results and DiscussionBy comparing various kmer length combinations across seven different classification algorithms, we found that B cell receptor-based cellsubset classification outperforms T cell receptor-based classification, achievingan average AUC of over 96%. …”
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Ecological Momentary Assessment of emotional dysregulation and outbursts among youth with ADHD: a feasibility study of a biomarker-driven predictive algorithm in the special education pre-K and early childhood classroom settings by Ripudaman (Zeeba) Singh, Janav Panchal, Sami Ali, Beth Krone, Isaac J. Wert, Mark Owens, Mark Stein, Maulik V. Shah

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Deep recurrent neural network with fractional addax optimization algorithm for influenza virus host prediction by Shweta Ashish Koparde, Sonali Kothari, Sharad Adsure, Kapil Netaji Vhatkar, Vinod V. Kimbahune

“…This research • Introduces a novel approach for predicting the host of influenza viruses by leveraging protein sequences. • Extraction of features, including sequence length, Amino Acid Composition (AAC), Dipeptide Composition (DPC), Tripeptide Composition (TPC), aromaticity, secondary structure fraction, and entropy from protein sequence. • Addresses the data imbalance and improves model generalization, the oversampling technique is applied for data augmentation.The prediction model employs a Deep Recurrent Neural Network (DRNN) optimized by Fractional Addax Optimization 34 Algorithm (FAOA), a hybrid of Addax Optimization Algorithm (AOA) and Fractional Concept (FC), designed to perform 35 influenza virus host prediction. …”
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