Automated detection of spreading depolarizations in electrocorticography by Sreekar Puchala, Ethan Muchnik, Anca Ralescu, Jed A. Hartings

“…SD detection using sparse sampling (0.1 Hz) is optimal for streaming and use in cloud computing applications for neurocritical care.…”
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Design of a Novel Fractional Whale Optimization-Enhanced Support Vector Regression (FWOA-SVR) Model for Accurate Solar Energy Forecasting by Abdul Wadood, Hani Albalawi, Aadel Mohammed Alatwi, Hafeez Anwar, Tariq Ali

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Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

“…This work employs single hidden layer extreme learning machine (ELM) algorithm and hybrid particle swarm optimization-based support vector regression (PS-SVR) for determining energy storage efficiency of high-entropy ceramics. …”
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Filter-enhanced adiabatic quantum computing on a digital quantum processor by Erenay Karacan, Conor Mc Keever, Michael Foss-Feig, David Hayes, Michael Lubasch

“…Eigenstate filters underpin near-optimal quantum algorithms for ground-state preparation. …”
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An Optimized Transformer–GAN–AE for Intrusion Detection in Edge and IIoT Systems: Experimental Insights from WUSTL-IIoT-2021, EdgeIIoTset, and TON_IoT Datasets by Ahmad Salehiyan, Pardis Sadatian Moghaddam, Masoud Kaveh

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Identification of a Time-Dependent Source Term in Multi-Term Time–Space Fractional Diffusion Equations by Yushan Li, Yuxuan Yang, Nanbo Chen

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High-performance computing for static security assessment of large power systems by Venkateswara Rao Kagita, Sanjaya Kumar Panda, Ram Krishan, P. Deepak Reddy, Jabba Aswanth

“…We perform extensive experiments to evaluate the efficacy of the proposed algorithm. As a result, we establish that the proposed parallel algorithm with high-performance computing (HPC) computing is much faster than the traditional algorithms. …”
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Scalable bearing fault diagnosis using metaheuristic feature selection and machine learning for diverse operating conditions by B. R. Nayana, R. Subha, Rekha Radhakrishnan, P. Geethanjali

“…The objective of this study is to develop a scalable model for real-time bearing fault diagnosis using recent evolutionary algorithms such as, Marine Predator Algorithm, Equilibrium Optimization, Henry Gas Solubility Optimization, and Poor and Rich Optimization for optimal Feature Selection. …”
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Computational Aspects of <i>L</i>₀ Linking in the Rasch Model by Alexander Robitzsch

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Research on dynamic prediction and optimization of high altitude photovoltaic power generation efficiency using GVSAO-CNN Model under 8-climate modes by Xiaoming Xiong, Heng Hu, Qiangfu Jia, Rongjian Zhang, Chongan Huang, Qingyuan Lu

“…The GVSAO algorithm is a sophisticated optimization technique that fine-tunes the hyperparameters of CNNs. …”
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Hybrid lion and exponential PSO-based metaheuristic clustering approach for efficient dynamic data stream management by M. Ananthi, K. Valarmathi, A. Ramathilagam, R. Praveen

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Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

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Reinforcement Learning for Computational Guidance of Launch Vehicle Upper Stage by Shiyao Li, Yushen Yan, Hao Qiao, Xin Guan, Xinguo Li

“…Computational guidance algorithms can deal with emergencies during flight and improve the success rate of missions, and most of the current computational guidance algorithms are based on optimal control, whose calculation efficiency cannot be guaranteed. …”
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Using the Genetic Algorithm in Developing a Method for Steganography by Nadia Mohammed

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DIDADTIC TOOLS FOR THE STUDENTS’ ALGORITHMIC THINKING DEVELOPMENT by T. P. Pushkaryeva, T. A. Stepanova, V. V. Kalitina

“…Modern engineers must possess high potential of cognitive abilities, in particular, the algorithmic thinking (AT). In this regard, the training of future experts (university graduates) of technical specialities has to provide the knowledge of principles and ways of designing of various algorithms, abilities to analyze them, and to choose the most optimal variants for engineering activity implementation. …”
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On the Performance of Linear Decreasing Inertia Weight Particle Swarm Optimization for Global Optimization by Martins Akugbe Arasomwan, Aderemi Oluyinka Adewumi

“…Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. …”
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Symbiotic Learning Grey Wolf Optimizer for Engineering and Power Flow Optimization Problems by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…Furthermore, two power flow problems namely, the optimal power flow (13 cases for IEEE 30 and 57-bus system) and optimal reactive power dispatch (8 cases for IEEE 30 and 57-bus system) from the recent literature are investigated. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…We also design an improved service allocation strategy, MESDA, based on the Gray Wolf Optimization (GWO) algorithm. MESDA dynamically adjusts its exploration and exploitation components, and introduces a random factor to enhance the algorithm’s ability to determine the direction during later stages. …”
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Firefly Algorithm for Polynomial Bézier Surface Parameterization by Akemi Gálvez, Andrés Iglesias

“…This paper solves the parameterization problem for polynomial Bézier surfaces by applying the firefly algorithm, a powerful nature-inspired metaheuristic algorithm introduced recently to address difficult optimization problems. …”
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A vectorization of iterative computational processes and time acceleration estimates by V. M. Demidenko, V. I. Benediktovich

“…A vector model for the implementation of sequential calculations is proposed, which takes into account  the  main  features  of  vector-conveyor computers. The  optimal  total  execution  time  of  sequential calculations in the vector mode is determined, and a lower estimate of the time gain is obtained in comparison with the sequential mode of their execution.C o n c l u s i o n. …”
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