Elite Evolutionary Discrete Particle Swarm Optimization for Recommendation Systems by Shanxian Lin, Yifei Yang, Yuichi Nagata, Haichuan Yang

“…The results establish EEDPSO as a robust optimization strategy for recommendation systems that effectively handles the cold-start problem.…”
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Developing an IoT and ML-driven platform for fruit ripeness evaluation and spoilage detection: A case study on bananas by Rajini M, Persis Voola

“…This framework employed various machine learning algorithms to detect ripeness stages, with the CatBoost classifier exhibiting exceptional performance, demonstrating its dependability and effectiveness in assessing fruit quality. …”
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A fashion product recommendation based on adaptive VPKNN-NET algorithm without fuzzy similar image by R. Sabitha, D. Sundar

“…It eliminates the limitations of fuzzy similarity models and offers a scalable solution for visually oriented e-commerce platforms, particularly in cold-start scenarios and low-data conditions.…”
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An Improved Salp Swarm Algorithm for Solving a Multi-Temperature Joint Distribution Route Optimization Problem by Yimei Chang, Jiaqi Yu, Yang Wang, Xiaoling Xie

“…To solve this model, an improved salp swarm algorithm (SSA) has been developed. The feasibility and effectiveness of both the proposed model and algorithm are demonstrated using R110 data from the Solomon standard calculation example. …”
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Experimental Investigation and NSGA-III Multi-Criteria Optimization of 60CrMoV18-5 Cold-Work Tool Steel Machinability Under Dry CNC Hard Turning Conditions by Nikolaos A. Fountas, Ioannis G. Papantoniou, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

“…This work concerns an experimental investigation dealing with the machinability of 60CrMoV18-5 cold-work tool steel under dry CNC hard turning conditions using a CBN cutting insert. …”
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Combining the SHAP Method and Machine Learning Algorithm for Desert Type Extraction and Change Analysis on the Qinghai–Tibetan Plateau by Ruijie Lu, Shulin Liu, Hanchen Duan, Wenping Kang, Ying Zhi

“…In this work, five different machine learning algorithms are used to classify different desert types on the Qinghai–Tibetan Plateau (QTP), and their classification performance is evaluated on the basis of their classification results and classification accuracy. …”
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Study on Short Term Temperature Forecast Model in Jiangxi Province based on LightGBM Machine Learning Algorithm by Kanghui SUN, An XIAO, Houjie XIA

“…In order to achieve further improvement in the forecast accuracy of station temperatures and enhance the forecast capability for extreme temperatures， this study establishes a 24-hour national station daily maximum （minimum） temperature forecast model for Jiangxi Province based on the LightGBM machine-learning algorithm and the MOS forecast framework by using the surface observation data of 91 national stations in Jiangxi Province and the upper-air and surface forecast data of the ECMWF model from 2017 to 2019.The results of the 2020 evaluation show that the LightGBM model daily maximum （minimum） temperature forecast is consistent with the observed trend， and the annual average forecast is better than that of three numerical models， ECMWF， CMA-SH9 and CMA-GFS， two machine learning products， RF and SVM， and subjective revision products.In terms of the spatial and temporal distribution of forecast errors， the model's daily maximum （minimum） temperature forecast errors in winter and spring are slightly larger than those in summer and autumn； the daily maximum temperature forecast errors show the spatial distribution characteristics of "larger in the south and smaller in the north， and larger in the periphery than in the centre"， while the opposite is true for the daily minimum temperatures.In terms of important weather processes， the LightGBM model has the best prediction effect among the seven products in the high temperature process； in the strong cold air process， the LightGBM model is still better than the three numerical model products and the other two machine-learning models， but the prediction effect of the daily minimum temperature is not as good as that of the subjective revision products.After a simple empirical correction for the low-temperature forecast error in the strong cold air process， the model low-temperature forecast effect is close to that of the subjective revision product.The model significance analysis shows that the recent surface observation features also contribute to the model construction， and the results can be used as a reference for model improvement and temperature forecast product development.At present， the LightGBM model temperature forecast products have been applied to meteorological operations in Jiangxi Province.…”
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Development of a river dissolved oxygen prediction model integrating spatial effects and multiple deep learning algorithm by Yubo Zhao, Mo Chen

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Elaboration of the Calculation Algorithm for the Load Diagram of a Thermoelectric Generator that Applies the Temperature Dependent Thermoelectric Layer Properties by Golubev R.O., Stolyarov S.P.

“…The aim of the work is the development of the algorithm for the working parameters calculation of a marine waste heat thermoelectric generator, where the thermoelectric layer properties are considered as temperature dependent. …”
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Research on Collaborative Optimization Method of CCHP Regional Integrated Energy System Based on Improved Multivariate Universe Algorithm by Dahai Xu, Changle Yu, Wenwen Li, Su Zhang, Zhengda Li, Zhihui Qu, Pengtao Li, Xingfan Han

“…By integrating Pareto theory, an adaptive grid method, and a roulette strategy into the multiverse algorithm, an enhanced multi-objective multiverse algorithm is developed, which notably enhances the convergence accuracy, convergence speed, and stability of the solutions. …”
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Snow parameter retrieval (SPR) algorithm for the GCOM-C/SGLI sensor: validation over the Greenland ice sheet by Nan Chen, Wei Li, Yongzhen Fan, Yingzhen Zhou, Teruo Aoki, Tomonori Tanikawa, Masashi Niwano, Masahiro Hori, Rigen Shimada, Sumito Matoba, Knut Stamnes

“…Application of the RTM-SciML algorithm to SGLI images obtained over the Greenland Ice Sheet revealed a significant change in snow parameters from a cold July 2018 to a warm July 2019. …”
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Analysis and validation of characteristic genes in RNA sequencing datasets from heart failure patients based on multiple algorithms by Yuxuan Li, Ying Bai, Wujiao Wang, Zhaotian Ma, Peng Li, Dong Li, Sinai Li, Jialin Jin, Jialin Jin, Qian Lin

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Integration of the reptile search algorithm and the adaptive neuro-fuzzy inference system enhances standardized precipitation evapotranspiration index forecasting by Zahra Kayhomayoon, Mohammad Javad Bahmani, Sami Ghordoyee Milan, Ommolbanin Bazrafshan, Ronny Berndtsson

“…Abstract A novel metaheuristic algorithm called the reptile search algorithm (RSA) was introduced in conjunction with artificial neural fuzzy inference system (ANFIS) for the estimation of standardized precipitation evapotranspiration index (SPEI). …”
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Tumor-immune partitioning and clustering algorithm for identifying tumor-immune cell spatial interaction signatures within the tumor microenvironment. by Mai Chan Lau, Jennifer Borowsky, Juha P Väyrynen, Koichiro Haruki, Melissa Zhao, Andressa Dias Costa, Simeng Gu, Annacarolina da Silva, Tomotaka Ugai, Kota Arima, Minh N Nguyen, Yasutoshi Takashima, Joe Yeong, David Tai, Tsuyoshi Hamada, Jochen K Lennerz, Charles S Fuchs, Catherine J Wu, Jeffrey A Meyerhardt, Shuji Ogino, Jonathan A Nowak

“…<h4>Results</h4>Six unsupervised TIPC subtypes based on T lymphocyte distribution patterns were identified, comprising two cold and four hot subtypes. Three of the four hot subtypes were associated with significantly longer colorectal cancer (CRC)-specific survival compared to a reference cold subtype. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…Experiments on the Amazon-Book and Last-FM datasets show that SKGRec significantly outperforms several state-of-the-art recommendation algorithms on the Recall@20 and NDCG@20 metrics. Comparison experiments validate the effectiveness of semantic analysis of user behavior and multi-hop path inference, while cold-start experiments further confirm the robustness of the model in sparse-data scenarios. …”
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The optimum sizing of zero-emission water-cooled VCR cycle based on exergo-economic-environmental assessment criteria by triple-objective MPSO by Seyedeh Mohadeseh Miri, Mahmood Farzaneh-Gord, Alireza Hosseinpour, Mohit Bajaj, Ievgen Zaitsev

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Data Temperature Informed Streaming for Optimising Large-Scale Multi-Tiered Storage by Dominic Davies-Tagg, Ashiq Anjum, Ali Zahir, Lu Liu, Muhammad Usman Yaseen, Nick Antonopoulos

“…This leads to the concept of hot and cold data. Cold data can be migrated away from high-performance nodes to free up performance for higher priority data. …”
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Multidimensional water-economic-ecological joint optimization for Manas River Basin, China, using a dual-population co-evolutionary algorithm by Jian Qin, Yongpeng Tong, Muhammad Arsalan Farid, Heng Zhang, Hao Tian, Xiaolong Li, Xinlin He, Lianqing Xue, Yi Li, Yongli Gao, Guang Yang

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Understudied targets of the ischemia-reperfusion injury pathogenesis in liver transplantation by P. O. Svishcheva, A. A. Kanibolotskiy, B. I. Yaremin, E. Yu. Anosova, Ya. S. Karina, Z. G. Kaziakhmedova, M. S. Novruzbekov

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Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm-Random Forest Regression by Muhammad Shahzad Nazir, Sami ud Din, Wahab Ali Shah, Majid Ali, Ali Yousaf Kharal, Ahmad N. Abdalla, Padmanaban Sanjeevikumar

“…The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). The test results show that the GSA-RFR model improves prediction accuracy and reduces the generalization error. …”
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