Extreme gradient and boosting algorithm for improved bias-correction and downscaling of CMIP6 GCM data across indian river basin by Chandni Thakur, Venkatesh Budamala, KS Kasiviswanathan, Claudia Teutschbein, Bankaru-Swamy Soundharajan

“…The effectiveness of the extreme gradient boosting framework in reproducing climate data was compared with the conventional quantile delta mapping approach across the basin. Additionally, both methods were evaluated across different seasons, including monsoon, pre-monsoon, and post-monsoon. …”
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Rendering algorithm for 3D model of goods in power warehouse based on linear interpolation and 2D texture mapping by Gui Luo, Xin Chen, Quan Liu, Anlin Liu, Xuan Zhang, Li Tian, Yueshi Gao

“…Thirdly, the designed mapping architecture maintains color accuracy below ΔE < 3.2 across illuminance levels of 50–1000 lx. …”
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Mapping sugarcane plantations in Northeast Thailand using multi-temporal data from multi-sensors and machine-learning algorithms by Savittri Ratanopad Suwanlee, Surasak Keawsomsee, Emma Izquierdo-Verdiguier, Jaturong Som-Ard, Alvaro Moreno-Martinez, Vorraveerukorn Veerachit, Jantima Polpinij, Kanokporn Rattanasuteerakul

“…The effectiveness of machine learning algorithms and the limited reference data introduce uncertainness for sugarcane classification. …”
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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT by Sefri Imanuel Fallo, Lidia Paskalia Nipu

“…This research is primarily dedicated to providing a comprehensive exposition of the methodology applied in the deployment of a cartographic-based machine learning algorithm designed for the precise identification of areas susceptible to landslides within the geographical confines of the Takari District.This research delves into the application of mapping-based machine learning algorithms in the domain of non-structural disaster mitigation, with a specific emphasis on the detection of landslide susceptibility within the Takari District. …”
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Review of machine learning algorithms used in groundwater availability studies in Africa: analysis of geological and climate input variables by Haoulata Touré, Cyril D. Boateng, Solomon S. R. Gidigasu, David D. Wemegah, Vera Mensah, Jeffrey N. A. Aryee, Marian A. Osei, Jesse Gilbert, Samuel K. Afful

“…Over the past ten years, machine learning has been increasingly and successfully used in groundwater availability studies across the world. This review paper explores the application of machine learning techniques in groundwater availability studies including groundwater level prediction and groundwater potential mapping studies by focusing on some of the studies conducted in Africa. …”
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Application of the Multi-Strategy Improved Walrus Optimization Algorithm in Mobile Robot Path Planning by Yongfu Ke, Limei Shi, Weinan Ji, Peng Luo, Lei Guo

“…Firstly, the Sine-Tent-Cosine chaotic mapping is used to initialize the walrus population, addressing the issue of insufficient population diversity in the later stages of the algorithm&#x2019;s iteration. …”
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An Improved Hybrid Ant Colony Optimization and Genetic Algorithm for Multi-Map Path Planning of Rescuing Robots in Mine Disaster Scenario by Jingrui Zhang, Zhenhong Xu, Houde Liu, Xiaojun Zhu, Bin Lan

“…Additionally, a grid-based, rectangular-area, obstacle avoidance strategy is incorporated to precisely evaluate the obstacle avoidance path of each individual across different obstacle maps. Finally, the feasibility and effectiveness of the proposed hybrid algorithm are validated through simulations involving both single and multiple mine disaster maps. …”
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Genetic algorithm optimization of ensemble learning approach for improved land cover and land use mapping: Application to Talassemtane National Park by Ali Azedou, Aouatif Amine, Isaya Kisekka, Said Lahssini

“…Accurate Land Cover/Land Use (LCLU) mapping is critical for protected area management, yet previous studies of Talassemtane National Park (TNP) in Morocco have produced coarse maps with limited accuracy. …”
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Mapping EQ-5D-5L Score From SGRQ in Patients with Asthma and/or COPD in NOVELTY by Jackson D, Quinton A, Zhang F, Müllerová H, Janson C, Sadatsafavi M

“…NOVELTY coefficients broaden the population with chronic airways disease for whom this mapping can be applied.Keywords: health status, utility mapping, longitudinal analysis, algorithm, economic modeling, quality of life…”
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Assessing the spatiotemporal dynamics of seasonal and perennial surface water resources across Lesotho’s agroecological zones by Kunwar K. Singh, Sayedeh Sara Sayedi, Ariel BenYishay, Tšepiso A. Rantšo

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A Novel Algorithm for a Low-Cost, Curvature-Continuous Smooth Path with Multiple Constraints on a Cost-Assigned Flat Map by Xu Du, Lu Yang

“…The method is divided into two stages: In the first stage, the graph structure is constructed by generating points on the map, and uses Dijkstra’s Algorithm to obtain the connection order of the landmark points. …”
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Comparison of Tree Typologies Mapping Using Random Forest Classifier Algorithm of PRISMA and Sentinel-2 Products in Different Areas of Central Italy by Eros Caputi, Gabriele Delogu, Alessio Patriarca, Miriam Perretta, Giulia Mancini, Lorenzo Boccia, Fabio Recanatesi, Maria Nicolina Ripa

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DBO-AWOA: An Adaptive Whale Optimization Algorithm for Global Optimization and UAV 3D Path Planning by Tao Xu, Chaoyue Chen

“…To address these challenges, this study introduces an adaptive whale optimization algorithm (DBO-AWOA), which incorporates chaotic mapping, nonlinear convergence factors, adaptive inertia mechanisms, and dung beetle optimizer-inspired reproductive behaviors. …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…Finally, the improved algorithm is applied to 3D map path planning simulations involving multiple nodes and obstacles, confirming its capability to enhance UAV robustness, adaptability, and real-time performance. …”
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A data-driven, cloud-based approach for forest aboveground biomass mapping using GEDI and other earth observation data: an ecoregion-specific Investigation across the state of Alab... by Janaki Sandamali, Lana L. Narine

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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…Second, we introduce a Position-Sensitive Channel Attention (PSCA) mechanism, which calculates spatial statistics (mean and standard deviation) across height and width dimensions for each channel feature map. …”
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Pathways to chronic disease detection and prediction: Mapping the potential of machine learning to the pathophysiological processes while navigating ethical challenges by Ebenezer Afrifa‐Yamoah, Eric Adua, Emmanuel Peprah‐Yamoah, Enoch O. Anto, Victor Opoku‐Yamoah, Emmanuel Acheampong, Michael J. Macartney, Rashid Hashmi

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Yield prediction, pest and disease diagnosis, soil fertility mapping, precision irrigation scheduling, and food quality assessment using machine learning and deep learning algorith... by S. Ajith, S. Vijayakumar, N. Elakkiya

“…This review synthesizes advancements in artificial intelligence applications across key domains, including crop yield prediction, precision irrigation, soil fertility mapping, insect pest and disease forecasting, and foodgrain quality assessment. …”
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Trade-off between cost and performance of earth observation data in olive trees health assessment: Digital crop mapping approach using machine learning algorithms by Yassine Bouslihim, Abdelkrim Bouasria, Aicha Rochdi, El Bachir El Haissen, Dénes Loczy, Zoltan Orban, Ali Salem

“…The RF model showed superior performance across all datasets, achieving the lowest RMSE values. …”
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Application of an improved pelican optimization algorithm based on comprehensive strategy in PV parameter identification by Xu Yong, Sang Bicong, Zhang Yi

“…Furthermore, this optimization method yields the smallest mean square error across all types of solar cells, demonstrating the superiority of the proposed algorithm.…”
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