Improved Variable Structure Interacting Multimodels for Target Trajectory Tracking and Extrapolation by Xuanming Ren, Xinmin Tang, Yang Zhou, Xiangmin Guan

“…To improve the lengthy computation time of conventional variable structure interacting multiple model (VSIMM) algorithm and increase the precision of target prediction and extrapolation, the target state and flight intent information captured by the Automatic Dependent Surveillance-Broadcast (ADS-B) are used as the model’s prior information; combining this information with VSIMM theoretical framework, we purpose an intent variable structure interacting multiple model (INT-VSIMM) algorithm. …”
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Prognosis of unfavorable course of ulcerative colitis as indication for anticytokine therapy by A. Yu. Baranovsky, E. A. Kondrashina, A. G. Kharitonov

“…Aim of investigation. To outline predictive model for unfavorable course of ulcerative colitis (UC).Material and methods. …”
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Ensemble and transfer learning of soil inorganic carbon with visible near-infrared spectra by Yu Wang, Keyang Yin, Bifeng Hu, Yongsheng Hong, Songchao Chen, Jing Liu, Lili Yang, Jie Peng, Zhou Shi

“…Therefore, we hypothesized that the use of the ensemble technique could further SIC prediction accuracy and have a better model transfer capability. …”
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Peningkatan Akurasi Metode Weighted Fuzzy Time Series Forecasting Menggunakan Algoritma Evolusi Differensial dan Fuzzy C-Means by Agus Fachrur Rozy, Solimun Solimun, Ni Wayan Surya Wardhani

“…Conventional prediction methods encounter difficulties in adapting data with the assumptions used, necessitating the application of the Weighted Fuzzy Time Series (WFTS) method. …”
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Near-Infrared Spectroscopy Combined With Support Vector Machine Model to Realize Quality Control of Ginkgolide Production by Lei Liu, Jun Wang, Haiyi Bian, Ahmed N. Abdalla

“…The collect extensive NIRS data throughout the ginkgolide production process and develop chemometric models using PLS, SVM, and random forest algorithms. These models are rigorously validated through cross-validation and independent testing to assess their accuracy and precision in predicting chemical content and classifying product stages. …”
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Reference-Free Assessment of Speech Intelligibility Using Bispectrum of an Auditory Neurogram. by Mohammad E Hossain, Wissam A Jassim, Muhammad S A Zilany

“…The proposed metric also had a wide dynamic range, and the predicted scores were well-separated as a function of hearing loss. …”
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Design and analysis of antenna through machine learning for next-generation IoT system by Rachit Jain, R. Ramya, Vandana Vikas Thakare, P. K. Singhal

“…Notably, the CatBoost algorithm demonstrates superior performance, achieving 77.4% accuracy in predicting antenna return loss. …”
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IMPLEMENTASI METODE RANDOM FOREST DALAM MEMPREDIKSI SINYAL PERGERAKAN SAHAM by MOCH. ANJAS APRIHARTHA, M. HUSNIYADI, TAUFIK NUR ALAM

“…Random forest is a combination algorithm of several decision trees used to solve prediction or classification problems. …”
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Characterization of the Collagen Extraction Manufacturing Process Using Markov Chains and Artificial Neural Networks by Rosa Trasvina-Osorio, Sergio Alonso-Romero, Juan de Anda-Suarez, Valentin Calzada-Ledesma, Javier Yanez-Mendiola, Luis Fernando Villanueva-Jimenez, Erick Rojas-Mancera

“…In the second stage, the predictive model MCMC-ANN presented a mean square error (MSE) of 0.00171, and a standard deviation (SD) of 0.00133. …”
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Optimal design of frame structures equipped with viscous dampers using machine learning techniques by Yi Wen, Jianze Wang, Jun Xu, Kaoshan Dai, Yuanfeng Shi, Reza Sharbati

“…The built models achieved an average R2 of 0.955 for the testing dataset, indicating a high level of predictive accuracy. Then, with the target of minimizing seismic responses of the structural system, the developed DP-based optimization algorithm effectively identifies the optimal damper arrangement for the considered three structure cases. …”
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Delta-radiomics Entropy Based on Tumor Heterogeneity Concept – Response Predictor to Irradiation for Unresectable/recurrent Glioblastoma by Camil Ciprian MIRESTEAN, Roxana Irina IANCU, Dragos Teodor IANCU

“…Radiomics, a new subdomain of artificial intelligence (AI), relies on advanced analysis in high-resolution medical imaging to establish diagnostic, prognostic and predictive models for clinical medicine. The variation of the delta-radiomics parameters analyzed within a tumor volume may be via tumor heterogeneity indirectly correlated with the response to treatment. …”
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Eecs-fl: energy-efficient client selection for federated learning in AIoT by Yiyang Zhang, Yiming Luo, Tao Yang, Xiaofeng Wu, Bo Hu

“…Experimental results show that incorporating WPT leads to a reduction in unit energy consumption by over 24.54%; while, the proposed algorithm achieves a reduction of over 15.31% compared to random selection. …”
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Gas adsorption meets geometric deep learning: points, set and match by Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis

“…Recently, machine learning (ML) pipelines have been established as the go-to method for large scale screening by means of predictive models. These are typically built in a descriptor-based manner, meaning that the structure must be first coarse-grained into a 1D fingerprint before it is fed to the ML algorithm. …”
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Magnetic resonance imaging of cruciate ligament disorders: current updates by Tanda Yang, Yexin Li, Longtao Yang, Qian Liu

“…AI plays a crucial role in automating radiological estimations and enabling data-driven predictions of future events. Despite the transformative impact of advanced MRI techniques on the analytical and diagnostic algorithms related to cruciate ligament disorders, future efforts are warranted to address challenges such as economic burdens and ethical considerations.…”
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Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

“…We synthesise these modalities by combining predictions from convolutional and graph neural networks with a multilayer perceptron. …”
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Performances Comparison for a Rotating Shaft Suspended by 4-Axis Radial Active Magnetic Bearings via 𝜇-Synthesis, Loop-Shaping Design, and Sub(𝐻)∞with Uncertainties by G. Barbaraci, G. Virzi' Mariotti

“…On contrary PID controller does not depend on angular speed and it can be easily implemented according some simple rules. Predictive control is another interesting controller characterized by a multiple controller operating in different condition in order to get the minimum of cost function, but also in this case the angular speed is introduce for the same reason discussed before.…”
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Use of ICT to Confront COVID-19 by Yousry Saber El Gamal

“…Risk prediction is one of the important AI applications during the Pandemic. …”
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Realtime Precise Orbit Determination Technology for LEO Mega-Constellation by Zhen LI, Chuang SHI

“…Supported by GNSS, it analyzed the advantages and disadvantages of solving LEO satellite orbit on the ground or onboard the satellites.The high-fidelity non-conservative force models were applied to the real-time orbit determination algorithm.To separate the kinematic and dynamic orbit determination process had been a great advantage for LEO satellites with much frequent orbital maneuvers.The test results showed that the accuracy of accelerations computed from the radiation pressure and atmospheric drag non-conservation force models were around 5 nm/s².Use the broadcast ephemeris, the real-time orbit determination algorithm could get an accuracy of 0.8 m in the satellites′ positions and 1.1 mm/s accuracy in the satellites′ velocity.When the real-time precise ephemeris of GNSS satellites were provided, the algorithm could get an accuracy of 8 cm in the LEO satellites′ position and 0.1 mm/s in the velocity.The method for real-time orbit determination and orbit prediction in this paper could be used to support the construction of navigation system with the mega-constellations.…”
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Dynamic Bayesian Network Model for Overhead Power Lines Affected by Hurricanes by Kehkashan Fatima, Hussain Shareef

“…To characterize the stochastic properties of HIF, Monte Carlo simulation (MCS) is employed in conjunction with fragility curves (FC) and the scenario reduction (SCENRED) algorithm. The proposed DBN model evaluates the probability of asset failure and compares the results using stochastic Monte Carlo simulation based on the fragility curve scenario reduction algorithm (FC-MCS-SCENRED) model. …”
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Occupant-Centric Visual Comfort Assessment and Optimization of Passive Solar Façade Shading Systems through View-Based Analysis of Daylight Glare Probability, View Content, and Spa... by Martin Ivanov, Jun Sato

“…The proposed framework employs an adaptive optimization algorithm that iteratively generates and refines shading device configurations, effectively balancing glare reduction, external visibility, and visual complexity. …”
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