Study on the Macroeconomic Model Based on the Genetic Algorithm by Sun Shihao, Yixin Zhou, Yong Wang, Wu Wang

“…In this study, genetic algorithm is introduced as the core algorithm. In the algorithm efficiency verification test, the calculation model based on genetic algorithm is constructed in Matlab environment, and the data space construction mode and genetic variation mode of genetic algorithm are explored. …”
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Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

“…In this study, we extend subsampling techniques to irregularly spaced time series data which are modeled by irregularly spaced autoregressive models. …”
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ALGORITHM FOR PLANNING PROJECTS by Y. N. Kondrashov, M. O. Chashchin

“…An ever-increasing difficulty and complexity of projects in various fields of human activities makes it necessary to improve the project planning algorithms at enterprises. …”
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An Improved LEACH Protocol for Optimizing Cluster Head Selection and In-cluster Selection by SHIBing, GAOZelin, SUNYueping, HUANJuan, SUNTao

“…Furthermore, these improvements confirm that the energy balance associated with the LEACH-enhance algorithm is superior, particularly in terms of cluster head selection and node entry.…”
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A tutorial on ‘capped utilisation’ as a metric and key performance target in NHS England’s Model Hospital operating theatres database: caution for international healthcare systems... by Chen Zhang, Claire Dunstan, Jaideep J. Pandit

“…This could serve as a model internationally, as other countries seek to improve operating theatre efficiency. …”
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Improving Acceptance to Sensory Substitution: A Study on the V2A-SS Learning Model Based on Information Processing Learning Theory by Kyeong Deok Moon, Yun Kyung Park, Moo Seop Kim, Chi Yoon Jeong

“…This improvement is significantly higher than the gain of 2.72% achieved by optimizing the V2A-SS algorithm with Mel-Scaled Frequency Mapping. …”
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An Improved Maximum Power Point Tracking Control Scheme for Photovoltaic Systems: Integrating Sparrow Search Algorithm-Optimized Support Vector Regression and Optimal Regulation fo... by Mingjun He, Ke Zhou, Yutao Xu, Jinsong Yu, Yangquan Qu, Xiankui Wen

“…However, achieving accurate tracking control while balancing overall performance in terms of stability, dynamic response, and robustness remains a challenge. In this study, an improved MPPT control scheme based on the technique of predicting the reference current at the MPP and regulating the optimal current is proposed. …”
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An Enhanced Multiple Object Tracking Method With Improved Feature Fusion and Cross-Camera Trajectory Matching for Closed Scenes by Fengjun Chen, Guangxun Zhu, Zhenyu Lv, Ke Wang, Ruiyan Xu, Jian Liu

“…Furthermore, a hierarchical association method based on ambiguous assignment modeling (HAAM) is proposed to improve the stability and robustness of object tracking in time series. …”
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Development of scientific and methodological approaches to improve the efficiency of quarry transport operation by A. N. Novikov, I. A. Novikov, N. A. Zagorodnij, A. S. Semykina

“…It is concluded that it is necessary to develop scientific and methodological approaches to improve the operation of open pit transport. An algorithm for the operation of open pit transport in a simulation model has been developed, which allows taking into account the influence of the control and distribution system of dump trucks on the number of excavators and the timely delivery of dump trucks to storage points. …”
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Combination of dynamic TOPMODEL and machine learning techniques to improve runoff prediction by Pin‐Chun Huang

“…The present study aims to evaluate the optimal combination of these parameters within the dynamic TOPMODEL framework using machine learning techniques to improve the accuracy of runoff predictions and bolster the model's reliability. …”
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Improving the streamflow prediction accuracy in sparse data regions: a fresh perspective on integrated hydrological-hydrodynamic and hybrid machine learning models by Saeed Khorram, Nima Jehbez

“…For each analysed series and residuals, the proposed model needs separate TCN-SARIMA models. This requires the ADPSO algorithm for parameter calibration, which elongates the computation time. …”
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Using 'sentinel' plants to improve early detection of invasive plant pathogens. by Francesca A Lovell-Read, Stephen Parnell, Nik J Cunniffe, Robin N Thompson

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Achieving comprehensive water productivity improvement: A multi-objective simulation-optimization model for water productivity-oriented irrigation water management by Gang Li, Chenglong Zhang, Zailin Huo, Yanqi Liu

“…Improving water productivity (WP) from multiple perspectives is crucial for irrigated agriculture in arid areas, particularly due to challenges such as low crop WP, limited economic returns, and secondary soil salinization. …”
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External validation of and improvement upon a model for the prediction of placenta accreta spectrum severity using prospectively collected multicenter ultrasound data by Magdalena Kolak, Stephen Gerry, Hubert Huras, Ammar Al Naimi, Karin A. Fox, Thorsten Braun, Vedran Stefanovic, Heleen vanBeekhuizen, Olivier Morel, Alexander Paping, Charline Bertholdt, Pavel Calda, Zdenek Lastuvka, Andrzej Jaworowski, Egle Savukyne, Sally Collins, IS‐PAS group

“…Abstract Introduction This study aimed to validate the Sargent risk stratification algorithm for the prediction of placenta accreta spectrum (PAS) severity using data collected from multiple centers and using the multicenter data to improve the model. …”
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Improving Forest Above-Ground Biomass Estimation Accuracy Using Multi-Source Remote Sensing and Optimized Least Absolute Shrinkage and Selection Operator Variable Selection Method by Er Wang, Tianbao Huang, Zhi Liu, Lei Bao, Binbing Guo, Zhibo Yu, Zihang Feng, Hongbin Luo, Guanglong Ou

“…Compared to the optimal SGBoost model with the Lasso variable selection method (R² of 0.69, RMSE of 18.63 Mg/ha), the VIF-Lasso method improves R² by 0.06 and reduces RMSE by 2.15 Mg/ha, while the Lasso-GA method improves R² by 0.04 and reduces RMSE by 1.93 Mg/ha. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…We generated a stratified 60‐20‐20 train‐validate‐test split to assess model generalizability. We trained four machine learning algorithms including logistic regression, Random Forest, AdaBoost and XGBoost. …”
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A Scalable Ensemble Learning-Based Model for Optimal Placement of Circuit Breaker and Sectionalizer in Power Distribution Systems with the Aim of Reliability Improvement by Mehrdad Ebrahimi, Mohammad Rastegar

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The Improving Effect of Intelligent Speech Recognition System on English Learning by Qi Luo

“…To improve the effect of English learning in the context of smart education, this study combines speech coding to improve the intelligent speech recognition algorithm, builds an intelligent English learning system, combines the characteristics of human ears, and studies a coding strategy of a psychoacoustic masking model based on the characteristics of human ears. …”
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Do Sharpness-Based Optimizers Improve Generalization in Medical Image Analysis? by Mohamed Hassan, Aleksandar Vakanski, Boyu Zhang, Min Xian

“…In recent years, significant research has focused on improving the generalization of deep learning models by regularizing the sharpness of the loss landscape. …”
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Improving the accuracy of honey bee forage class mapping using ensemble learning and multi-source satellite data in Google Earth Engine by Filagot Mengistu, Binyam Tesfaw Hailu, Temesgen Alemayehu Abera, Janne Heiskanen, Tadesse Terefe Zeleke, Tino Johansson, Petri Pellikka

“…Nonetheless, the highest overall accuracy (94.7 %) was obtained when integrating the four machine learning algorithms in an Ensemble Learning Approach (ELA). Applying ELA improved the classification accuracy by 3.8 %, 6.5 %, 9.2 %, and 14.8 % compared to single learner classification algorithms (i.e., GTB, RF, CART, and SVM, respectively). …”
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