Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction by Jingjing Chen, Dan Zhang, Chengxiu Zhu, Lin Lin, Kejun Ye, Ying Hua, Mengjia Peng

“…Functional enrichment analyses delineated the dysregulation of pathways, while weighted gene co-expression network analysis identified hub genes within ribosome biogenesis-associated modules. A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …”
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Apply Ridge Regression Model to Predict the Lateral Velocity Difference of Tight Reservoirs by HAN Longfei, ZHANG Yongfei, WANG Miaomiao, LI Yu

“…Finally, a ridge regression algorithm is used to establish a prediction model of the lateral wave time lag based on the logging data of five wells in WQ block. …”
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Efficient Channel Prediction Technique Using AMC and Deep Learning Algorithm for 5G (NR) mMTC Devices by Vipin Sharma, Rajeev Kumar Arya, Sandeep Kumar

“…In this paper, we have proposed a channel prediction scheme based on a deep learning (DL) algorithm possessed by parametric analysis. …”
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Mobile application based on KDD to predict high-crime areas and promote sustainability in citizen security in a district of Lima-Perú by Hugo Vega-Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza, Gisella Luisa Elena Maquen-Niño, Luis Guerra-Grados, Jorge Pantoja-Collantes, Oscar Benito-Pacheco, Juan Carlos Lázaro-Guillermo, Adegundo Camara-Figueroa, Javier Cabrera-Díaz, Rubén Gil-Calvo, Frida López-Córdova

“…The data mining process follows the KDD methodology, which includes the stages of selection, preprocessing, transformation, data mining, evaluation and knowledge consolidation. Machine learning algorithms, such as Random Forest and Gradient Boosting, were used to make these predictions. …”
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A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques by Cong Peng, Cheng Gong, Xiaoya Zhang, Duxian Liu

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Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

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Non-Destructive Methods Based on Machine Learning for the Prediction of Sweet Potato Leaf Area: A Comparative Approach by Joao Everthon Da Silva Ribeiro, Ester Dos Santos Coelho, Antonio Gideilson Correia Da Silva, Pablo Henrique De Almeida Oliveira, Elania Freire Da Silva, Gisele Lopes Dos Santos, Anna Kezia Soares De Oliveira, John Victor Lucas Lima, Walter Esfrain Pereira, Lindomar Maria Da Silveira, Aurelio Paes Barros

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On Solving System of Linear Differential-Algebraic Equations Using Reduction Algorithm by Srinivasarao Thota

“…In this paper, we present a new reduction algorithm for solving system of linear differential-algebraic equations with power series coefficients. …”
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Model Order Reduction by Legendre Expansion Using Harmony Search Algorithm by Hasan Nasiri Soloklo, Malihe Maghfoori Farsangi

Subjects: “…Harmony search algorithm…”
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MIMO System Reduction Using Modified Pole Clustering and Genetic Algorithm by C. B. Vishwakarma, R. Prasad

“…This method guarantees stability of the reduced model if the original high-order system is stable. The algorithm of the proposed method is illustrated with the help of an example and the results are compared with the other well-known reduction techniques.…”
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Optimizing Lattice Basis Reduction Algorithm on ARM V8 Processors by Ronghui Cao, Julong Wang, Liming Zheng, Jincheng Zhou, Haodong Wang, Tiaojie Xiao, Chunye Gong

“…The LLL (Lenstra–Lenstra–Lovász) algorithm is an important method for lattice basis reduction and has broad applications in computer algebra, cryptography, number theory, and combinatorial optimization. …”
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Efficient PAPR reduction algorithm in OFDM based on nonlinear piecewise companding by Zhitong XING, Yun LI, Deyi PENG, Bensi ZHANG, Kaiming LIU, Yuan’an LIU

“…Focusing on the high peak-to-average power ratio （PAPR） problem in orthogonal frequency division multiplexing （OFDM） systems， a generalized hybrid of rayleigh and sine distribution based nonlinear companding algorithm for PAPR reduction in OFDM systems was provided.For the proposed algorithm， signal samples with small amplitudes remain unchanged.For the signal samples with large amplitudes， their probability density function were changed from rayleigh distribution to sine-based distribution.The proposed algorithm can effectively reduce the PAPR， and at the same time， maintain the bit error rate performance and power spectral density performance.Simulation results indicate that with the same PAPR performance， compared with referred companding schemes， the proposed algorithm has lower bit error rate and out of band radiation.…”
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GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM by Nasir A. Al-Awad, Izz K. Abboud, Muaayed F. Al-Rawi

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N-Dimensional Reduction Algorithm for Learning from Demonstration Path Planning by Juliana Manrique-Cordoba, Miguel Ángel de la Casa-Lillo, José María Sabater-Navarro

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Reduction algorithm based on supervised discriminant projection for network security data by Fangfang GUO, Hongwu LYU, Weilin REN, Ruini WANG

“…In response to the problem that for dimensionality reduction, traditional manifold learning algorithm did not consider the raw data category information, and the degree of clustering was generally at a low level, a manifold learning dimensionality reduction algorithm with supervised discriminant projection (SDP) was proposed to improve the dimensionality reduction effects of network security data.On the basis of the nearest neighbor matrix, the label information of the raw data category was exploited to construct a supervised discriminant matrix in order to translate unsupervised popular learning into supervised learning.The target was to find a low dimensional projective space with both maximum global divergence matrix and minimum local divergence matrix, ensuring that the same kind of data was concentrated and heterogeneous data was scattered after dimensionality reduction projection.The experimental results show that the SDP algorithm, compared with the traditional dimensionality reduction algorithms, can effectively remove redundant data with low time complexity.Meanwhile the data after dimensionality reduction is more concentrated, and the heterogeneous samples are more dispersed, suitable for the actual network security data analysis model.…”
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A Fast Hybrid Classification Algorithm with Feature Reduction for Medical Images by Hanan Ahmed Hosni Mahmoud, Abeer Abdulaziz AlArfaj, Alaaeldin M. Hafez

“…In this paper, we are introducing a fast hybrid fuzzy classification algorithm with feature reduction for medical images. …”
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Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark by Marios C. Gkikas, Dimitris C. Gkikas, Gerasimos Vonitsanos, John A. Theodorou, Spyros Sioutas

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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…This manuscript proposes the Predictive Analytics of Complex Healthcare Systems Using the DL-based Disease Diagnosis Model (PACHS-DLBDDM) method. …”
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A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging by Jian Zhang, Jiajin Wang, Hongbo Li, Qin Zhang, Xiangning He, Cui Meng, Xiaoyan Huang, Youtong Fang, Jianwei Wu

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ON DESIGN OF PREDICTIVE MODEL FOR HEART DISEASE by Soumyendu Bhattacharjee, Susmita Das, Sangita Roy, Arpita Santra, Anasuya Sarkar, Moumita Pa, Biswarup Neogi

“…We create a coronary disease prediction model based on the patient's clinical history to assess whether or not the patient is most likely to develop a coronary illness. …”
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