Study on the Method of Vineyard Information Extraction Based on Spectral and Texture Features of GF-6 Satellite Imagery by Xuemei Han, Huichun Ye, Yue Zhang, Chaojia Nie, Fu Wen

“…Moreover, the RF model, which amalgamates spectral and texture features, exhibits a notable 13.59% increase in accuracy versus the spectral-only model and a 14.92% improvement over the texture-only model. …”
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Inversion of snow geophysical parameters using the VHR PAZ X-band dual polarimetric SAR data: first known experiments in the Himalayan region by Hemant Singh, Divyesh Varade

“…In the present work, we utilized the copolar phase difference (CPD) for SD and Integral Equation model (IEM) for snow density. In this study, we proposed an improved algorithm for SD inversion, instead of relying on a single in-situ snow density value, we incorporated a range of snow densities (0.15 to 0.27 g/cm3), optimizing the axial ratio between 1.13 and 1.17. …”
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A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…Traditional energy management methods, based on static models or heuristic algorithms, often fail to handle real-time grid dynamics, leading to suboptimal energy distribution, high operational costs, and significant energy wastage. …”
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Short-Term Traffic Flow Forecasting Model Based on GA-TCN by Rongji Zhang, Feng Sun, Ziwen Song, Xiaolin Wang, Yingcui Du, Shulong Dong

“…Therefore, a short-term traffic flow forecasting model GA-TCN based on genetic algorithm (GA) optimized time convolutional neural network (TCN) is proposed in this paper. …”
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Adaptive machine learning framework: Predicting UHPC performance from data to modelling by Yinzhang He, Shaojie Gao, Yan Li, Yongsheng Guan, Jiupeng Zhang, Dongliang Hu

“…LightGBM demonstrated the most stable performance among all models. As the number of features decreased, model performance initially increased then decreased, peaking at FS_14 (test set: R2 = 0.9677, MAE = 4.4621 MPa, RMSE = 6.9226 MPa), showing the mutual information scoring method can improve the model performance by reducing redundant information. …”
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Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…The direction for further research is to improve the ant algorithm.…”
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Parallel Bayesian Optimization of Thermophysical Properties of Low Thermal Conductivity Materials Using the Transient Plane Source Method in the Body-Fitted Coordinate by Huijuan Su, Jianye Kang, Yan Li, Mingxin Lyu, Yanhua Lai, Zhen Dong

“…A parallel Bayesian optimization algorithm based on a multi-objective hybrid strategy (MHS) is proposed based on an inverse problem. …”
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Research on productivity prediction method of infilling well based on improved LSTM neural network: A case study of the middle-deep shale gas in South Sichuan by GUAN Wenjie, PENG Xiaolong, ZHU Suyang, YANG Chen, PENG Zhen, MA Xiaoran

“…Two stage-specific models were constructed, with the number of hidden layer neurons, dropout rate, and batch size determined by the optimal solutions obtained via GWO. …”
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Enhancing the prediction of vitamin D deficiency levels using an integrated approach of deep learning and evolutionary computing by Ahmed Alzahrani, Muhammad Zubair Asghar

“…To improve the models effectiveness and guarantee the optimal choice of the features and hyper-parameters, we incorporate evolutionary computing methods, particularly genetic algorithms (GA). …”
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An enhanced YOLOv8 model for accurate detection of solid floating waste by Juxing Di, Kaikai Xi, Yang Yang

“…The new model optimizes the feature fusion strategy in the neck, constructing a refined “160-80-40-20” multiscale detection frame work. …”
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Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network by Qiuxia Fan, Xinqi Zhang, Zhuang Wen, Lei Xu, Qianqian Zhang

“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
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MRI based early Temporal Lobe Epilepsy detection using DGWO based optimized HAETN and Fuzzy-AAL Segmentation Framework (FASF). by Hasim Khan, Ahmed Ibrahim Alutaibi, Ghanshyam G Tejani, Sunil Kumar Sharma, Ahmad Raza Khan, Fuzail Ahmad, Seyed Jalaleddin Mousavirad

“…Furthermore, an effective feature selection method is proposed using the Dipper- grey wolf optimization (DGWO) algorithm to improve the performance of the proposed model. …”
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Optimizing intelligent reflecting surface assisted visible light communication networks under blockage and practical constraints using TLBO for IoT applications by Vipul Dixit, Ajit Kumar, Nishant Sharan, Shikha Pandey, Atul Kumar, Ram Sewak Singh

“…Additionally, detailed convergence analysis demonstrates that TLBO performs better than Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) in terms of convergence speed, higher fitness value and lower sensitivity to initial conditions, making it most suitable for real-time IRS-VLC based IoT applications.…”
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Optimal control strategy based on artificial intelligence applied to a continuous dark fermentation reactor for energy recovery from organic wastes by Kelly Joel Gurubel Tun, Elizabeth León-Becerril, Octavio García-Depraect

“…This strategy has demonstrated to be a viable algorithm for real-time control applications. First, experimental data from continuous dark fermentation are modeled using support vector machine (SVM) algorithm for response prediction and then, optimization algorithms are employed to identify the key parameters that enhance H2 production. …”
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Model of a Novel PCB Coil for High-Sensitivity Metal Detector by Han Zhang, Mingxing Song, Yuejiu Zhu, Xianze Xu, Fengqiu Xu

“…An optimization problem is constructed from the numerical model, and the optimal design parameters of the receiving coil are determined via a heuristic algorithm. …”
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The applications of CT with artificial intelligence in the prognostic model of idiopathic pulmonary fibrosis by Zeyu Chen, Zheng Lin, Zihan Lin, Qi Zhang, Haoyun Zhang, Haiwen Li, Qing Chang, Jianqi Sun, Feng Li

“…The potential improvements of AI in CT assessments, including time-series CT analysis, optimization of AI algorithms, utilization of multi-modal data, and discovery of new biomarkers through unsupervised algorithms, could be introduced to make a more accurate and convenient assessment for the prognosis of IPF patients. …”
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From Pairwise Comparisons of Complex Behavior to an Overall Performance Rank: A Novel Alloy Design Strategy by Rafael Herschberg, Lisa Rateau, Laure Martinelli, Fanny Balbaud-Célérier, Jean Dhers, Anna Fraczkiewicz, Gérard Ramstein, Franck Tancret

“…In this case, the method is applied to the design of wear-resistant hard-facing alloys by also associating it with a combinatorial optimization of their composition by a multi-objective genetic algorithm. …”
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Application of KTA-KELM in Fault Diagnosis of Rolling Bearing by Zhuo Wang, Wenjun Zhao, Tao Ma, Zhijun Li, Bo Qin

“…Then，the Kernel Target Alignment（KTA） parameters of maximum KTA value Ai and the kernel parameter σi are initialized, and the different kernel parameter values are adjusted by judging the distance between the kernel matrix and the ideal target matrix，so as to obtain the minimum corresponding maximum kernel arrangement value when the kernel matrix distance is obtained，and the kernel parameter at this time is optimal. Finally，the high-dimensional feature vector set of the above rolling bearing is used as input to learn the KTA-KELM algorithm, the state recognition model of rolling bearing is built based on KTA-KELM algorithm. …”
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Leveraging ultrasonic-derived phenotypes and estimated breeding value to improve abdominal fat weight prediction in chickens throughout the egg laying period by Penghao Li, Zhengda Li, Fan Ying, Dan Zhu, Dawei Liu, Xianyi Song, Jie Wen, Guiping Zhao, Bingxing An

“…While, AFT measured by ultrasound improved the predictive ability of all the models (R² of KNN showed highest increase of 12.35 %). …”
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Training Large Models on Heterogeneous and Geo-Distributed Resource with Constricted Networks by Zan Zong, Minkun Guo, Mingshu Zhai, Yinan Tang, Jianjiang Li, Jidong Zhai

“…To achieve this goal, we formulate the model partitioning problem among heterogeneous hardware and introduce a hierarchical searching algorithm to solve the optimization problem. …”
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