Application of a hybrid algorithm of LSTM and Transformer based on random search optimization for improving rainfall-runoff simulation by Wenzhong Li, Chengshuai Liu, Caihong Hu, Chaojie Niu, Runxi Li, Ming Li, Yingying Xu, Lu Tian

“…Abstract Flood forecasting using traditional physical hydrology models requires consideration of multiple complex physical processes including the spatio-temporal distribution of rainfall, the spatial heterogeneity of watershed sub-surface characteristics, and runoff generation and routing behaviours. …”
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Phenotypic and Genetic Diversity Analysis of 18 Ornamental Strawberries by Chaocui Nong, Jiayi Hou, Jin He, Yanju Zheng, Shugen Yang, Lai Jiang, Qian Xie, Wei Wang, Jinghua Wu, Qingxi Chen, Lixiang Miao

“…Notably, ‘Summer Breeze-Rose’ and ‘Summer Breeze-Cherry’ possess relatively complex genetic backgrounds (Q < 0.6). Furthermore, the floral, foliar, and plant traits of both germplasms display significant ornamental value and can serve as vital resources for the development and utilization of ornamental strawberries, as well as for the selection and breeding of new varieties.…”
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Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles by Jian Liu, Shuai Kang, Juan Ren, Dongxia Zhang, Bing Niu, Kai Xu

“…Optimal needle trajectory selection is critical in biopsy procedures to minimize tissue damage and ensure diagnostic accuracy. …”
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Predicting pile bearing capacity using gene expression programming with SHapley Additive exPlanation interpretation by Adil Khan, Majid Khan, Waseem Akhtar Khan, Muhammad Ali Afridi, Khawaja Atif Naseem, Ayesha Noreen

“…GEP is a computational technique that mimics biological gene expression processes to evolve computer programs or models capable of solving complex problems through the iterative generation, selection, and recombination of code segments. …”
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Machine Learning-Based Morphological Classification and Diversity Analysis of Ornamental Pumpkin Seeds by Sıtkı Ermiş, Uğur Ercan, Aylin Kabaş, Önder Kabaş, Georgiana Moiceanu

“…<i>ovifera</i>) seeds are highly morphologically variable, and their classification is hence a complex task for the seed industry. Efficient and accurate classification is critical for agricultural production, breeding programs, and seed sorting for commerce. …”
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Machine Learning Modeling of Foam Concrete Performance: Predicting Mechanical Strength and Thermal Conductivity from Material Compositions by Leifa Li, Wangwen Sun, Askar Ayti, Wangping Chen, Zhuangzhuang Liu, Lauren Y. Gómez-Zamorano

“…To overcome the limitations of traditional empirical models in capturing complex nonlinear relationships, a predictive framework with eight machine learning algorithms was established. …”
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Environmental, Genetic and Structural Interactions Affecting <i>Phytophthora</i> spp. in Citrus: Insights from Mixed Modelling and Mediation Analysis to Support Agroecological Prac... by Dalal Boudoudou, Majid Mounir, Mohamed El bakkali, Allal Douira, Hamid Benyahia

“…This study investigates the complex interactions between environmental, genetic, and structural factors that influence two key parameters: the density of <i>Phytophthora</i> spp. propagules per gram of dry soil (NPSS) and the number of colonies (NC). …”
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Monitoring of Energy Efficiency of District Heating System Facilities: Methodology for Determining the Energy Baseline by Davydenko L.V., Davydenko N.V., Davydenko V.A., Sprake D.

“…The selection of better structures of the mathematical model was realized based on the criteria for its appropriate-ness (regularity, unbiasedness criterion, Schwartz, determination coefficient) and accuracy of the forecast using the morphological criterion. …”
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Presenting a model for the establishment and maintenance of expert human resources in the government organizations of Sistan and Baluchestan province by Majid Reza Dahmardeh, Vahid pourshahabi, Amin Reza Kamalian, Habibollah Salaerzehi

“…The results show that in this research, the dimensions of maintaining expert human resources include: behavioral, structural, contextual, and normative/attitudinal factors; and 31 components, based on the output of structural equation analysis and path analysis technique, the path coefficient of behavioral factors is 0.901, structural factors 0.886, contextual 0.821, and normative/attitudinal 0.840, in which the behavioral factors have the greatest impact and the job satisfaction component with a significant number obtained from the T-test equals 24.004 and the path coefficient 0.901 has played the greatest role in maintaining expert human resources in the government organizations of Sistan and Baluchistan provinceExtended abstractIntroductionHuman capital is considered the most complex and valuable capital in any organization, which plays the main role in realizing the organization's goals. …”
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Air Temperature Modeling Based on Land Surface Factors by the Cubist Method (Case Study of Hamoun International Wetland) by Farhad Zolfaghari, Hasan Khosravi, Shahram Khalighi Sigaroudi

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EVALUATION OF SEWAGE WITHIN MAKHACHKALA BY CHEMICAL PARAMETERS by A. Sh. Ramazanov, M. A. Kasparova, I. V. Saraeva

“…Found that wastewater selected in two paragraphs refer to quality very dirty, 7 points extremely dirty; in all samples of wastewater content from 6 to 10 standardized components exceeds the MCL and the coefficient of the complex water pollution 7 samples belong to category II and contamination of sample 2 to Category III contamination.Main conclusion. …”
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Transforming Prediction into Decision: Leveraging Transformer-Long Short-Term Memory Networks and Automatic Control for Enhanced Water Treatment Efficiency and Sustainability by Cheng Qiu, Qingchuan Li, Jiang Jing, Ningbo Tan, Jieping Wu, Mingxi Wang, Qianglin Li

“…NH₃-N concentration serves as a key indicator of treatment efficiency and environmental impact; however, its complex dynamics and the scarcity of measurements pose significant challenges for accurate prediction. …”
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NEW MEAT PRODUCTS WITH IMMUNOMODULATORY EFFECT CREATION METHOD by I. V. Kaltovich, O. V. Dymar

“…New meat products with immunomodulatory effect creation method reflecting differential characteristics of technological stages of manufacture of those types of meat products, including issues on the selection of primary and secondary raw materials, guidelines for development of formulations and production technologies, legislative requirements towards its labeling, etc, has been developed for the first time. …”
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Runoff Forecasting Research Coupling Quadratic Factor Screening and Deep Learning by CHENG Liwen, HUANG Shengzhi, LI Pei, LI Ziyan, JIA Songtao, HUANG Qiang

“…The effective screening of factors influencing runoff is a key aspect of runoff forecasting research.However,there are many factors affecting runoff,and these factors have complex interactions.Most of the existing studies use numerically driven models with primary factor screening,and the results show that the input factors are spatially redundant,leading to poor forecasting results.In view of this,the support vector regression (SVR) and the long-short memory network model (LSTM) are compared with Weihe River Basin as an example,and the LSTM model is selected as the optimal forecasting model.Principal component analysis and gray correlation analysis are used for secondary screening of the input terms to form a model coupling principal component analysis,gray correlation analysis,and LSTM.The results show that:①the fitting accuracy of LSTM is higher than that of SVR;②the secondary screening of the input terms improves the forecast accuracy,and the forecast accuracy of the coupled model is better than that of the single model,specifically,the model accuracy evaluation indexes of the coupled model are substantially improved compared with those of the single model;③the Nash efficiency coefficient and deterministic coefficient of the coupled model of gray system correlation analysis are improved by 0.13% and 0.03%,respectively,compared with those of the coupled model of principal component analysis,and the standard deviation ratio of observed values is improved by 42.9%.The study shows that the secondary factor screening by using gray correlation can effectively improve forecast accuracy.…”
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Regression Analysis to Predict the Length of Time to Complete a Thesis based on the Title by Al Aminuddin, Rahmat Hidayat, Gita Sastria, Astried Astried

“…In general, the difficulty or complexity of the thesis can be reflected through the title of the thesis that is appointed. …”
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The Study of Constructivistic Learning Experience, Democratic Attitude, Learning Independence & Learning Motivation of Senior High School Students at Wajo Regency South Sulawesi by Muhammad Arafah, Syamsu Rijal, Sumarni, Suriyah Satar, Besse Sulfiani

“…SEM results show that constructivist biology learning experiences positively influence learning motivation (path coefficient = 0.228), as does learning independence (path coefficient = 0.430). …”
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Statistical mechanics of dynamical system identification by Andrei A. Klishin, Joseph Bakarji, J. Nathan Kutz, Krithika Manohar

“…To establish this analogy, we define the hyperparameter optimization procedure as a two-level Bayesian inference problem that separates variable selection from coefficient inference and enables the computation of the posterior parameter distribution in closed form. …”
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A data-driven PCA-RF-VIM method to identify key factors driving post-fracturing gas production of tight reservoirs by Yifan Zhao, Xiaofan Li, Lei Zuo, Zhongtai Hu, Liangbin Dou, Huagui Yu, Tiantai Li, Jun Lu

“…Hydraulic fracturing technology has achieved remarkable results in improving the production of tight gas reservoirs, but its effectiveness is under the joint action of multiple factors of complexity. Traditional analysis methods have limitations in dealing with these complex and interrelated factors, and it is difficult to fully reveal the actual contribution of each factor to the production. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The algorithms (RF and STR) with the smallest Mean Absolute Error (MAE) and the highest residual error (RMSE) and the highest correlation coefficient (RP2) were selected for further parameter optimization and evaluation. …”
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Noise Directivity Reconstruction Radiated from Unmanned Underwater Vehicle’s Propeller Using the Equivalent Source Method by Shuai Jiang, Liwen Tan, Ruichong Gu, Zilong Peng

“…In this paper, a method for selecting elementary source configurations was proposed, considering the correlation coefficients that exhibit a strong correlation with the directivity function. …”
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