Review of pedestrian trajectory prediction methods by Linhui LI, Bin ZHOU, Weiwei REN, Jing LIAN

“…With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected.…”
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TIRDH: A Novel Three-Shadow-Image Reversible Data Hiding Algorithm Using Weight and Modulo by Li-Chian Chin, Yu-Chen Li, Hung-Mo Hsieh, Chung-Ming Wang

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Prediction of the 180 day functional outcomes in aneurysmal subarachnoid hemorrhage using an optimized XGBoost model by Weichong Zhou, Xingfu Liao, Hui Shi, Mingfeng Wang, Yunchong Xiao, Xilu Yu, Yilong Wu, YanYi Liu, Yin Peng, Hai Su

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One-point Method for Speed Strategy Optimization Based on Slope Simplification and Speed Limit Prediction by XING Jian, HAN Bing

Subjects: “…speed limit prediction…”
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Vessel Traffic Flow Prediction in Port Waterways Based on POA-CNN-BiGRU Model by Yumiao Chang, Jianwen Ma, Long Sun, Zeqiu Ma, Yue Zhou

“…Aiming at the stage characteristics of vessel traffic in port waterways in time sequence, which leads to complexity of data in the prediction process and difficulty in adjusting the model parameters, a convolutional neural network (CNN) based on the optimization of the pelican algorithm (POA) and the combination of bi-directional gated recurrent units (BiGRUs) is proposed as a prediction model, and the POA algorithm is used to search for optimized hyper-parameters, and then the iterative optimization of the optimal parameter combinations is input into the best combination of iteratively found parameters, which is input into the CNN-BiGRU model structure for training and prediction. …”
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A composite photovoltaic power prediction optimization model based on nonlinear meteorological factors analysis and hybrid deep learning framework by Mengji Yang, Haiqing Zhang, Xi Yu, Aicha Sekhari Seklouli, Abdelaziz Bouras, Yacine Ouzrout

Subjects: “…Photovoltaic power prediction…”
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Diabetes Mellitus Disease Prediction and Type Classification Involving Predictive Modeling Using Machine Learning Techniques and Classifiers by B. Shamreen Ahamed, Meenakshi S. Arya, S. K. B. Sangeetha, Nancy V. Auxilia Osvin

“…Various Machine-Learning (ML) algorithms are being used in order to predict and detect the disease to avoid further complications of health. …”
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Synthetic graphs for link prediction benchmarking by Alexey Vlaskin, Eduardo G Altmann

“…Predicting missing links in complex networks requires algorithms that are able to explore statistical regularities in the existing data. …”
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Research on the Photovoltaic MPPT Method Based on Improved BP-SVM-ELM Combination Prediction by DAI Bowang, ZHAO Xianggui, ZHU Qiliang

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Predicting and Preventing Crime: A Crime Prediction Model Using San Francisco Crime Data by Classification Techniques by Muzammil Khan, Azmat Ali, Yasser Alharbi

“…The study proposes a crime prediction model by analyzing and comparing three known prediction classification algorithms: Naive Bayes, Random Forest, and Gradient Boosting Decision Tree. …”
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Research on the Performance of Vehicle Lateral Control Algorithm Based on Vehicle Speed Variation by Weihai Zhang, Jinbo Wang, Tongjia Pang

Subjects: “…model predictive control algorithm…”
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Heat transfer and simulated coronary circulation system optimization algorithms for real power loss reduction by Kanagasabai L.

“…In this paper, the heat transfer optimization (HTO) algorithm and simulated coronary circulation system (SCCS) optimization algorithm has been designed for Real power loss reduction. …”
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Exploring quantum control landscape and solution space complexity through optimization algorithms and dimensionality reduction by Haftu W. Fentaw, Steve Campbell, Simon Caton

“…Evaluations of traditional control techniques and machine learning algorithms reveal that Genetic Algorithms (GA) outperform Stochastic Gradient Descent (SGD), while Q-learning (QL) shows great promise compared to Deep Q-Networks (DQN) and Proximal Policy Optimization (PPO). …”
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Cooperative Sleep and Energy-Sharing Strategy for a Heterogeneous 5G Base Station Microgrid System Integrated with Deep Learning and an Improved MOEA/D Algorithm by Ming Yan, Tuanfa Qin, Wenhao Guo, Yongle Hu

“…Numerical results indicate that our approach achieves significant energy savings while ensuring accurate predictions of BSMG energy demands through a multi-objective evolutionary algorithm based on decomposition.…”
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Lifetime Prediction of Power IGBT Module by WANG Yan-gang, Chamund Dinesh, LI Shi-ping, Jones Steve, DOU Ze-chun, XIN Lan-yuan, LIU Guo-you

“…The Weibull methodology for power cycling test data and some reported typical lifetime models were firstly discussed. Then, lifetime prediction procedures were presented including the conversion of mission profile to temperature profile, the temperature cycles counting by Rainflow algorithm, and lifetime calculating based on the fatigue linear accumulation damage theory and lifetime models. …”
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Explainable Machine Learning in the Prediction of Depression by Christina Mimikou, Christos Kokkotis, Dimitrios Tsiptsios, Konstantinos Tsamakis, Stella Savvidou, Lillian Modig, Foteini Christidi, Antonia Kaltsatou, Triantafyllos Doskas, Christoph Mueller, Aspasia Serdari, Kostas Anagnostopoulos, Gregory Tripsianis

“…<b>Results:</b> The XGBoost classifier demonstrated the highest performance on the test dataset to predict depression with excellent accuracy (97.83%), with NNs a close second (accuracy, 97.02%). …”
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Travel time prediction for an intelligent transportation system based on a data-driven feature selection method considering temporal correlation by Amirreza Kandiri, Ramin Ghiasi, Maria Nogal, Rui Teixeira

“…In this study, a two-stage methodology is proposed which consists of two layers of Optimisation Algorithm and one Data-Driven method (OA2DD) to enhance the accuracy and efficiency of travel-time prediction. …”
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Genetic prediction of male pattern baldness. by Saskia P Hagenaars, W David Hill, Sarah E Harris, Stuart J Ritchie, Gail Davies, David C Liewald, Catharine R Gale, David J Porteous, Ian J Deary, Riccardo E Marioni

“…By splitting the cohort into a discovery sample of 40,000 and target sample of 12,000, we developed a prediction algorithm based entirely on common genetic variants that discriminated (AUC = 0.78, sensitivity = 0.74, specificity = 0.69, PPV = 59%, NPV = 82%) those with no hair loss from those with severe hair loss. …”
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Conformational ensembles for protein structure prediction by Jiaan Yang, Wen Xiang Cheng, Peng Zhang, Gang Wu, Si Tong Sheng, Junjie Yang, Suwen Zhao, Qiyue Hu, Wenxin Ji, Qiong Shi

“…The P53_HUMAN as a well-known protein and LEF1_HUMAN and Q8GT36_SPIOL as typical disordered proteins are token as the benchmark to evaluate the predicted outcomes. The results demonstrated an effective algorithm and biological meaningful process well to predict protein multiple conformation structures.…”
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Online Prediction Method for Power System Frequency Response Analysis Based on Swarm Intelligence Fusion Model by Lin Xu, Li Li, Meiying Wang, Xiangxu Wang, Yicong Li, Weidong Li, Kuanjiu Zhou

Subjects: “…Transient response prediction…”
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