An ensemble of deep representation learning with metaheuristic optimisation algorithm for critical health monitoring using internet of medical things by Mai Alduailij

“…For the feature selection process, the binary grey wolf optimization (BGWO) model is employed to identify and retain the most significant features in the dataset. …”
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Improved Splitting-Integrating Methods for Image Geometric Transformations: Error Analysis and Applications by Hung-Tsai Huang, Zi-Cai Li, Yimin Wei, Ching Yee Suen

“…The splitting-integrating method (SIM) is well suited to the inverse transformation <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>T</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula> of digital images and patterns, but it encounters difficulties in nonlinear solutions for the forward transformation <i>T</i>. We propose improved techniques that entirely bypass nonlinear solutions for <i>T</i>, simplify numerical algorithms and reduce computational costs. …”
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Efficient Rollout Algorithms for Resource-Constrained Project Scheduling with a Flexible Project Structure and Uncertain Activity Durations by Chunlai Yu, Xiaoming Wang, Qingxin Chen

“…The common random numbers technique not only enhances computational efficiency but also improves the accuracy of action selection. The post-rollout algorithm reduces computation time by 44.37% compared to the one-step rollout, with only a 0.02% performance gap. …”
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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

“…Nano-modified concrete has attracted wide attention due to its improved mechanical properties. Among them, compressive strength is the most critical indicator. …”
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Meta-Features Extracted from Use of kNN Regressor to Improve Sugarcane Crop Yield Prediction by Luiz Antonio Falaguasta Barbosa, Ivan Rizzo Guilherme, Daniel Carlos Guimarães Pedronette, Bruno Tisseyre

“…A comparative analysis is presented with a projection based on the Uniform Manifold Approximation and Projection (UMAP) algorithm, showing that MFs had more proximity than the original features when projected, which demonstrates that MFs revealed a clear formation of well-defined clusters, with most points within each group sharing the same color, suggesting greater uniformity in the predicted values. …”
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Structural design and optimization of egg carrier for dynamic egg slit detection platforms. by Ronghua Meng, Yuxiang Tian, Siwei Huang

“…Finally, motion simulation is carried out for the improved egg carrier, which verifies the optimized structure reasonableness.…”
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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…The Wilcoxon test results indicated that there was no significant difference between ABC_DEE and GABC, but ABC_DEE significantly outperformed the other algorithms. When <italic>D</italic>=20, ABC_DEE was superior to the comparison algorithms on at least 47 functions and inferior on at most 26 functions. …”
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Formulation and evaluation of ocean dynamics problems as optimization problems for quantum annealing machines. by Takuro Matsuta, Ryo Furue

“…We cast the linear partial differential equation governing the Stommel model into an optimization problem by the least-squares method and discretize the cost function in two ways: finite difference and truncated basis expansion. …”
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FORECASTING AND OPTIMIZATION OF CATALYTIC CRACKING UNIT OPERATION UNDER CONDITIONS OF FUZZY INFORMATION by Narkez Boranbayeva, Batyr Orazbayev, Leila Rzayeva, Zhalal Karabayev, Murat Alibek, Baktygul Assanova

“…The paper presents a procedure for developing and applying nonlinear regression models, describes algorithms for synthesizing linguistic models, and provides examples of their use to optimize the operation of catalytic cracking units. …”
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Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

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Optimal Low-Carbon Scheduling for Smart Microgrids With Dynamic Thermal Capacity Constraints by Peng Xie, Hongwei Liu, Chun Chen, Mingjun Liu

“…This study proposes a two-stage day-ahead robust optimization framework for the microgrids, integrating tri-level min-max-min modeling to address multidimensional uncertainties through parameterized uncertainty sets to balance conservatism and optimize costs under worst-case scenarios. …”
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Self-tuning trajectory tracking control for concrete pouring construction robots based on PID-NFTSMC and CPO algorithm. by Siwen Fan, Wanli Li, Rui Xie

“…Additionally, the study employed the crested porcupine optimizer (CPO) algorithm to automatically optimize PID control gains and NFTSMC sliding surface parameters, ensuring adaptability across varying conditions. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Optimization results indicated a theoretical 4% productivity gain and a 3 percentage point yield improvement, while exposing critical design constraints in the HGMS chamber.These findings underscore the potential of digital twins to accelerate process optimization and reduce development costs through in-silico experimentation. …”
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Engineering project management technology based on visual simulation module and particle swarm optimization by Hua Tian

“…The particle swarm multi-objective optimization algorithm performed well in reducing project cost prediction errors. …”
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Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…The hybrid algorithm's primary characteristic is its capacity to simultaneously fulfil multiple objectives, including reducing response times, enhancing resource efficiency, and decreasing operational costs. …”
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K-Means Clustering Algorithm Measuring the Satisfaction Level of MNC TV Muslim I'murojaah Program Viewers by Herayati Herayati, Andronias Siregar, Hariyanto Hariyanto

“…Recommendations for program improvement include enhancing image and sound quality, ensuring that the equipment and technology used can produce optimal quality. …”
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Enhancing Coverage and Efficiency in Wireless Sensor Networks: A Review of Optimization Techniques by Rajasekaran S, Shaik Mastan Vali

“…To address these issues, coverage optimization techniques are employed to maximize spatial coverage while minimizing energy consumption and deployment costs. …”
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Advancing GNOS-R Soil Moisture Estimation: A Multi-Angle Retrieval Algorithm for FY-3E by Xuerui Wu, Junming Xia, Weihua Bai, Yueqiang Sun

“…By leveraging multi-angle data, the algorithm achieves significantly improved retrieval accuracy, with root mean square errors of 0.0235, 0.0264, and 0.0191 (g/cm³) for bare, low-vegetation, and dense-vegetation areas, respectively. …”
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A VNS-NPGA approach to multi-objective optimization of hub-and-spoke logistics network by Changxi Ma, Chuwei Shi, Yun Yang, Yongpeng Zhao, Zhuye Xu, Bo Du

“…To realize low-cost freight transport in the logistics network and improve the network operation efficiency, a multi-objective optimization model and the corresponding algorithm for a hub-and-spoke logistics network are proposed based on the multi-level location of hub points and channels layout. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…The optimized VToMe-BiGRU algorithm combines the Transformer model and the BiGRU network, which effectively captures the critical features in the electric drive system data, thus improving the fault prediction performance. …”
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