A spatiotemporal graph wavelet neural network for traffic flow prediction by Linjie Zhang, Jianfeng Ma

“…The traffic flow prediction is fast becoming a key instrument in the transportation system, which has achieved impressive performance for traffic management. …”
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Surface water quality prediction based on BOA-BiLSTM model(基于BOA-BiLSTM模型的地表水水质预测) by 章佩丽(ZHANG Peili), 赵文雅(ZHAO Wenya), 许旭敏(XU Xumin), 包鑫磊(BAO Xinlei)

“…The results indicate that the predicted RMSE of NH3—N by the BOA-BiLSTM model for the next four hours is respectively 0.213 2, 0.368 9, 0.332 7 and 0.374 0, the predicted RMSE of TP is respectively 0.024 6, 0.032 1, 0.042 2 and 0.033 4. …”
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A Destination Prediction Network Based on Spatiotemporal Data for Bike-Sharing by Jian Jiang, Fei Lin, Jin Fan, Hang Lv, Jia Wu

“…The model, called destination prediction network based on spatiotemporal data (DPNst), comprises three steps. …”
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Prediction of Environmentally Suitable Areas for <i>Zephyranthes</i> (Amaryllidaceae) in Mexico by Zayner Edin Rodríguez Flores, Yanet Moredia Rosete, Jesús Alejandro Ruiz Valencia, Yolanda Leticia Fernández Pavía

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An Online-Traffic-Prediction Based Route Finding Mechanism for Smart City by Xiaoguang Niu, Ying Zhu, Qingqing Cao, Xining Zhang, Wei Xie, Kun Zheng

“…Finding fastest driving routes is significant for the intelligent transportation system. While predicting the online traffic conditions of road segments entails a variety of challenges, it contributes much to travel time prediction accuracy. …”
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Multi-Head Spatiotemporal Attention Graph Convolutional Network for Traffic Prediction by Ariyo Oluwasanmi, Muhammad Umar Aftab, Zhiguang Qin, Muhammad Shahzad Sarfraz, Yang Yu, Hafiz Tayyab Rauf

“…By achieving 91.8% accuracy on the Los Angeles highway traffic (Los-loop) test data for 15-min traffic prediction and an R2 score of 85% on the Shenzhen City (SZ-taxi) test dataset for 15- and 30-min predictions, the proposed model demonstrated that it can learn the global spatial variation and the dynamic temporal sequence of traffic data over time. …”
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Efficient Seismic Denoising Transformer with Gradient Prediction and Parameter-Free Attention by GAO Lei, QIAO Haowei, LIANG Dongsheng, MIN Fan, YANG Mei

“…For the problem of denoising seismic data, an efficient Transformer model with gradient prediction and parameter-free attention (ETGP) is proposed. …”
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Predicting prognosis and immunotherapy response of ferroptosis-related genes in colorectal cancer by Hongyun Wei, Keyu Ren, Yanchun Jin, Yao Wen, Bin Cao, Yu Gan, Ying Shi, Zhihong Wu, Linlin Chen

“…A total of 135 ferroptosis-associated genes were identified, with the high-risk subgroup having significantly worse overall survival. The prognostic model showed strong predictive power. Immunohistochemistry (IHC) assay showed that Sorting Nexin 5 (SNX5) and Ubiquitin-specific protease 7 (USP7) were significantly up-regulated in CRC tissues compared with adjacent CRC tissues. …”
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Seismic prediction of Permian volcanic rock reservoirs in Southwest Sichuan Basin by Chen Fei, Liu Shugen, Yong Ziquan

“…The study aims to analyze Permian volcanic reservoirs (VResr) in the Chengdu Janyang area in the southwestern part of the Sichuan Basin through seismic prediction (SP) techniques in order to identify and predict VResr. …”
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Evaluation of Encoder-Only Transformer for Multi-Step Traffic Flow Prediction by Mas Omar, Fitri Yakub, Andika Aji Wijaya, Ahmad Faiz Mohammad, Mohd Nazmin Maslan, Inge Dhamanti, Shi Zhongchao

“…The existing basic Encoder-Decoder Transformer model for multi-step prediction requires high computational complexity, making them less efficient for real-time applications. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…We propose an Edge Location Prediction Model (ELPM) suitable for the MEC scenario, which integrates Spatial-Temporal Graph Neural Networks and attention mechanisms. …”
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Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad, Vaisali Chandrasekar, Omar Aboumarzouk, Ajay Vikram Singh, Sarada Prasad Dakua

“…It is noted that spatial relationships within molecules are crucial in predicting hERG blockers. …”
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The microenvironment cell index is a novel indicator for the prognosis and therapeutic regimen selection of cancers by Xian-Yan Yang, Nian Chen, Qian Wen, Yu Zhou, Tao Zhang, Ji Zhou, Cheng-Hui Liang, Li-Ping Han, Xiao-Ya Wang, Qing-Mei Kang, Xiao-Xia Zheng, Xue-Jia Zhai, Hong-Ying Jiang, Tian-Hua Shen, Jin-Wei Xiao, Yu-Xin Zou, Yun Deng, Shuang Lin, Jiang-Jie Duan, Jun Wang, Shi-Cang Yu

“…Furthermore, combined with the spatial distribution characteristics of the six types of MCs, an MCI-enhanced (MCI-e) model was constructed, which could predict the prognosis of the TNBC patients more accurately. …”
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Predicting and delineating soil temperature regimes of China using pedotransfer function by Wan-kui BAO, Qiu-liang LEI, Zhuo-dong JIANG, Fu-jun SUN, Tian-peng ZHANG, Ning HU, Qiu-bing WANG

“…A zonal pedotransfer function (PTF) was developed based on the ensemble linear regression kriging model to predict the MAST50 in three topographic steps of China. …”
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Analysis and prediction of urban agglomeration ecological footprint based on improved three-dimensional ecological footprint and shared socioeconomic pathways by Ruirui Jiang, Liangjun Fei, Shouxuan Kang

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Optimal Harvesting for an Age-Spatial-Structured Population Dynamic Model with External Mortality by Yong Han Kang, Mi Jin Lee, Il Hyo Jung

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Predicting Potentially Suitable Habitats and Analyzing the Distribution Patterns of the Rare and Endangered Genus <i>Syndiclis</i> Hook. f. (Lauraceae) in China by Lang Huang, Weihao Yao, Xu Xiao, Yang Zhang, Rui Chen, Yanbing Yang, Zhi Li

“…In this study, we employed the MaxEnt model, integrated with geographic information systems (ArcGIS), to predict the potential distribution of <i>Syndiclis</i> under current and future climate scenarios, identify dominant bioclimatic drivers, and assess temporal and spatial shifts in habitat patterns. …”
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Spatial distribution model of anoa, Bubalus spp., in Tanjung Peropa Wildlife Reserve by Ola Aso, Abdul Mustari, Lilik Prasetyo

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Improved urban runoff prediction using high-resolution land-use, imperviousness, and stormwater infrastructure data applied to a process-based ecohydrological model. by Jonathan Halama, Robert McKane, Bradley Barnhart, Paul Pettus, Allen Brookes, Kevin Djang, Vivian Phan, Sonali Chokshi, James Graham

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Comparative evaluation of machine learning models for extreme river water level forecasting in Bangladesh: Implications for flood and drought resilience by Md Touhidul Islam, Sujan Chandra Roy, Nusrat Jahan, Al-Mahmud, Md Mazharul Islam, Abdullah Al Ferdaus, Kazunori Fujisawa, A.K.M. Adham

“…This study compares nine machine learning (ML) models for predicting monthly maximum and minimum water levels at three key stations along the Old Brahmaputra River using a 34-year dataset (1990–2024). …”
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