Advancing risk assessment in renewable power plant construction: an integrated DEA-SVM approach by Reza Rasinojehdehi, Seyyed Najafi

“…Subsequently, a SVM is developed to monitor the process, concluding with tailored risk treatment and monitoring processes specifically designed for the unique context of Iran's solar energy landscape.…”
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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…Dark fermentation process from low-cost renewable substrates for simultaneous wastewater treatment and hydrogen production (H2) is suitable due to economic viability and environmental sustainability. …”
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Group-Specific SVM With Bilevel Programming Methods for Parameter Optimization and Explainable AI in Urban Quality of Life Prediction by Gonzalo Rios-Vasquez, Hanns De La Fuente-Mella, Jose Ceroni-Diaz

“…A key contribution is the development of a Support Vector Machine (SVM) model for group-specific regression, enhanced by a bilevel programming reformulation that optimizes the hyperparameters of the model over groups of data. …”
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Forest cover restoration analysis using remote sensing and machine learning in central Malawi by Jabulani Nyengere, Precious Masuku, Sylvester Chikabvumbwa, Weston Mwase, Msaiwale Kathewera, Allena Laura Njala, Wilson Tchongwe, Isaac Tchuwa, Tiwonge I Mzumara, Chikondi Chisenga, Wilfred Kadewa, Emmanuel Chinkaka, Harineck Tholo

“…This study employs remote sensing and machine learning techniques to evaluate the effectiveness of such interventions in a village forest area in central Malawi. Utilizing a Support Vector Machine (SVM) classification algorithm applied to time-series Landsat and high-resolution imagery (2003–2023), we quantify land cover changes, while Normalized Difference Vegetation Index (NDVI) trends serve as indicators of ecological recovery. …”
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Approximate Symmetries and Conservation Laws for Mechanical Systems Described by Mixed Derivative Perturbed PDEs by Shamaoon A., Agarwal P., Cesarano C., Jain S.

“…In response to this challenge, we embarked on the rectification process. By integrating these additional terms into our model, we could modify the conserved vectors, deriving new modified conserved vectors. …”
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Investigation of cell development and tissue structure network based on natural Language processing of scRNA-seq data by Suwen Wei, Yuer Lu, Peng Wang, Qichao Li, Jianwei Shuai, Qi Zhao, Hai Lin, Yuming Peng

“…Using word2vec to embed gene sequences derived from gene networks, we generate vector representations of genes, which are then used to represent cells by summing gene vectors and subsequently tissues by aggregating cell vectors. …”
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Iterative Signal Processing for Blind Code Phase Acquisition of CDMA 1x Signals for Radio Spectrum Monitoring by Ron Kerr, John Lodge

“…The approach models the combination of the long-code generator and the two short-code generators, along with the pair-wise processing, by a single linear system over GF(2), with the initial states of the long- and short-code generators forming the input vector. …”
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Interpretable Machine Learning for High-Accuracy Reservoir Temperature Prediction in Geothermal Energy Systems by Mohammadali Ahmadi

“…This study conducts a comprehensive comparative analysis of advanced machine learning models, including support vector regression (SVR), random forest (RF), Gaussian process regression (GP), deep neural networks (DNN), and graph neural networks (GNN), to evaluate their predictive performance for reservoir temperature estimation. …”
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Artistic life of North Ossetia in the context of socio-political and economic changes (1991-2001) by Z. A. Turgieva

“…The reforming of the state structure in the early 90s of the XX century affected all spheres of social life in Russia, which largely determined the vector of further development of artistic culture. …”
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Predicting biogas production in real scale anaerobic digester under dynamic conditions with machine learning approach by M. Erdem Isenkul, Sevgi Güneş-Durak, Yasemin Poyraz Kocak, İnci Pir, Mertol Tüfekci, Güler Türkoğlu Demirkol, Selçuk Sevgen, Aslı Seyhan Çığgın, Neşe Tüfekci

“…Biogas production through anaerobic digestion (AD) of industrial organic waste and wastewater offers a sustainable method for energy recovery. However, since process efficiency heavily relies on operational factors, continuous monitoring of the AD process and the implementation of necessary operational strategies are crucial. …”
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Prediction of Rheological Parameters of Polymers by Machine Learning Methods by T. N. Kondratieva, A. S. Chepurnenko

“…Along with these methods, due to the capability to process data with highly nonlinear dependences between features, machine learning methods such as the k-nearest neighbor method, and the support vector machine (SVM) method, are widely used in related areas. …”
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Short-Term Load Forecasting Based on Feature Selection and Combination Model by Yusong XU, Shanhua ZOU, Xianling LU

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CLASSIFICATION AND PREDICTION OF BENTHIC HABITAT FROM SCIENTIFIC ECHOSOUNDER DATA: APPLICATION OF MACHINE LEARNING ALGORITHMS by Baigo HAMUNA, Sri PUJIYATI, Jonson Lumban GAOL, Totok HESTIRIANOTO

“…The classification and prediction process of benthic habitats uses two machine learning algorithms, Random Forest (RF) and Support Vector Machine (SVM), in XLSTAT Basic+ software. …”
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Research on Tilt Correction Algorithms of Destorted Data Matrix Code Image by GUAN Bo-yi, DONG Jing-wei, MA Xiao-feng, XU Bo

“…First, the LoG operator is used to detect the edge of the binary image, and then based on the structural features of the Data Matrix code, the location of the locator “L” is quickly determined by the Hough transform, and the “L” intersection point is expressed with two vectors. By vector cross product the rotation angle of Data Matrix code is calculated and the direction of rotation is determined then. …”
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Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…Spent fuel reprocessing is an important nuclear energy process which aimed at recovering resources and managing radioactive materials to control potential hazards. …”

Neural network recognition algorithm of breath sounds based on SVM by Gou-dong LIU, Jing XU

“…A SVM neural network (support vector machines) for breath sounds recognition algorithm was advanced,breath sounds feature obtained through wavelet analysis were input into neural networks and carried on the training to the training samples as a feature of SVM method input in order to classify the test samples.Three States (normal,mild and severe lesions) of breath sounds were recognized,and K nearest neighbor (KNN) methods are compared .The results show that SVM method has a higher recognition accuracy and can be used to recognize different breath sounds,which settled the local extremum problem that cannot be avoided in the neural network method and provide an effective algorithm for information processing in body area network technology.…”
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New anisotropic diffusion method to improve radiographic image quality by Mohamed B. Gharsallah, Ezzedine B. Braiek

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Modeling and Analysis of Dynamics of Rigid–Flexible Coupled Parallel Robots by Leilei Wang, Wei Xu, Fei Guo, Hao Yan, Yunxue Wang

“…Rigid–flexible coupled robots have problems such as vibration and elastic deformation caused by the flexibility of the members during the motion process, which significantly impacts the system’s motion accuracy and dynamics performance. …”
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Structure and Principles of Operation of a Quaternion VLSI Multiplier by Aleksandr Cariow, Mariusz Naumowicz, Andrzej Handkiewicz

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HashTrie:a space-efficient multiple string matching algorithm by Ping ZHANG, Yan-bing LIU, Jing YU, Jian-long TAN

“…The famous multiple string matching algorithm AC consumed huge memory when the string signatures were massive,thus unable to process high speed network traffic efficiently.To solve this problem,a space-efficient multiple string matching algorithm-HashTrie was proposed.This algorithm adopted recursive hash function to store the patterns in bit-vectors in place of the state transition table in order to reduce space consumption.Further more it made use of the rank operation for fast verification.Theoretic analysis shows that the space complexity of HashTrie is O(|P|),which is linear with the size of pattern set |P|and is independent of the alphabetsize σ.The space complexity is superior to the complexity O(|P|σlog|P|)of AC.Experiments on synthetic datasets and real-world datasets(such as Snort,ClamAV and URL)show that HashTrie saves up to 99.6% storage cost compared with AC,and in the meanwhile it runs at a matching speed that is about half of AC.HashTrie is a space-efficient multiple string matching algorithm that is appropriate to search large scale pattern strings with short lengths.…”
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