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GPS Position Prediction Method Based on Chaotic Map-Based Flower Pollination Algorithm

COMPLEXITY 2021年第1期2021卷

作者： Yang, Wanjun Sun, Zengwu Chongqing Finance & Econ Coll Chongqing Key Lab Spatial Data Min & Big Data Int Chongqing 401320 Peoples R China Shandong First Med Univ Coll Med Informat Engn Tai An 271016 Shandong Peoples R China Shandong Acad Med Sci Tai An 271016 Shandong Peoples R China

GPS position data prediction can effectively alleviate urban traffic, population flow, route planning, etc. It has very important research significance. Using swarm intelligence optimization algorithm to predict geographic location has important research strategies. Flower pollination algorithm (FPA) is a new swarm intelligence optimization algorithm (SIOA) and easy to implement and has other characteristics;more and more scholars have continuously improved it and applied it to more fields. Aiming at the fact that FPA leads to the local optimal value in cross-pollination, the chaotic mapping strategy is proposed to optimize related issues that the population is not rich enough in the self-pollination process. The improved flower pollination algorithm has better advantages in testing function convergence and geographic location prediction effect.

关键词： Global positioning system

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Agent-based modelling and simulation for life-cycle airport flight planning and scheduling

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JOURNAL OF SIMULATION 2024年第1期18卷 15-28页

作者： Ma, Xiaoyu He, Zhou Yang, Pengfei Liao, Xiyang Liu, Wei Beijing Foreign Studies Univ Int Business Sch Beijing Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing Peoples R China Chinese Acad Sci Key Lab Big Data Min & Knowledge Management Beijing Peoples R China UCAS UCASMOE Social Sci Lab Digital Econ Forecasts & Po MOE Social Sci Lab Digital Econ Forecasts & Policy Beijing Peoples R China Shenzhen Wanwei Zhilian Technol Co Ltd Headquarters Execut Off Shenzhen Peoples R China Univ Edinburgh Coll Sci & Engn Sch Informat Edinburgh Scotland Kings Coll London Dept Engn London England Univ Chinese Acad Sci Sch Econ & Management 3 Zhongguancun Nanyitiao Beijing 100190 Peoples R China

The airport flight planning and scheduling (AFPS) process involves many sub-systems in airport management, including flight arrival prediction, flight landing prioritisation, flight route scheduling, flight departure prioritisation and airport big-data planning. Existing literature has mainly focused on advancing the efficiency of specific sub-system(s) of AFPS. Therefore, there is a call to investigate the AFPS comprehensively and improve its performance systematically, instead of solely enhancing partial sub-system(s) in an airport. This paper proposes a life cycle analysis (LCA) framework to describe the "life cycle" that how an aircraft interacts with the AFPS system of an airport. The agent-based modelling and simulation technique is used to simulate the AFPS system under the LCA framework by treating each aircraft as a passive agent following the orders from the AFPS system. We demonstrate that the naive first-in-first-out principle can be modified to some simple prioritising rules to significantly reduce the overall delay (including importance-weighted delay) and processing time of flights, as well as to increase the number of departed aircraft. Hence, the produced agent-based model allows us to improve AFPS performance by optimising multiple sub-systems simultaneously.

关键词： Simulation agent-based modelling airport flight planning scheduling

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Developing Improved Time-Series DMSP-OLS-Like data (19922019) in China by integrating DMSP-OLS and SNPP-VIIRS

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2022年 60卷 1页

作者： Wu, Yizhen Shi, Kaifang Chen, Zuoqi Liu, Shirao Chang, Zhijian Southwest Univ Sch Geog Sci Chongqing Jinfo Mt Karst Ecosyst Natl Observat & Chongqing 400715 Peoples R China Southwest Univ Sch Geog Sci Chongqing Engn Res Ctr Remote Sensing Big Data Ap Chongqing 400715 Peoples R China Fuzhou Univ Key Lab Spatial Data Min & Informat Sharing Minist Educ Natl & Local Joint Engn Res Ctr Satellite Geospat Fuzhou 35002 Peoples R China

Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) and Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS) data are valuable records of nighttime lights (NTLs) in analyzing socioeconomic development. However, inconsistencies between these data have severely restricted long time-series analyses. Published time-series NTL data sets are not widely available or accurate because the DMSP-OLS calibration is inadequate and some missing data in the SNPP-VIIRS data are seldom considered for patching. To address these issues, we calibrated DMSP-OLS data (1992 & x2013;2013) by using a quadratic model based on a & x201C;pseudo-invariant pixel & x201D;method. Thereafter, an exponential smoothing model was used to predict and patch missing data in the monthly SNPP-VIIRS data (2013 & x2013;2019). Outliers and noise were also removed from the annual data. In addition, a sigmoid model was employed to generate improved simulated DMSP-OLS (SDMSP-OLS) data (2013 & x2013;2019), which were appended with the calibrated DMSP-OLS data (1992 & x2013;2013) to develop improved DMSP-OLS-like data (1992 & x2013;2019) in China. Finally, we qualitatively and quantitatively compared these data with published NTL data to examine data availability. Results showed that choosing invariant pixels to calibrate DMSP-OLS data can minimize discontinuity. The correlation between the SNPP-VIIRS data synthesized by the patched monthly SNPP-VIIRS data and the official annual SNPP-VIIRS data in 2015and 2016 was higher than those of the two existing correction methods with values below 0.90. spatial patterns of pixels in the improved SDMSP-OLS data in 2013 were more similar with the DMSP-OLS data than those in the published data. Strong correlations likewise existed between the total (average) pixel values of the improved SDMSP-OLS data (2013 & x2013;2019) and the DMSP-OLS data in 2012. We also found that the improved DMSP-OLS-like data hel

关键词： data models Urban areas Calibration spatial resolution Economic indicators data mining Correlation China Defense Meteorological Satellite Program Operational Linescan System (DMSP-OLS) integration nighttime light (NTL) data Suomi National Polar-orbiting Partnership Visible Infrared Imaging Radiometer Suite (SNPP-VIIRS) time-series

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Assessment of heavy metal pollution in agricultural soil around a gold mining area in Yitong County, China, based on satellite hyperspectral imagery

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JOURNAL OF APPLIED REMOTE SENSING 2021年第4期15卷

作者： Wu, Fuyu Wang, Xue Liu, Zhaoxian Ding, Jianwei Tan, Kun Chen, Yu China Univ Min & Technol MNR Key Lab Land Environm & Disaster Monitoring Xuzhou Jiangsu Peoples R China East China Normal Univ Minist Educ Key Lab Geog Informat Sci Shanghai Peoples R China East China Normal Univ Key Lab Spatial Temporal Big Data Anal & Applicat Minist Nat Resources Shanghai Peoples R China Second Surveying & Mapping Inst Hebei Shijiazhuang Hebei Peoples R China

Soil is one of the essential natural resources that is at risk from heavy metal pollution. The traditional sampling method for soil heavy metal monitoring and assessment cannot meet the requirements for large-scale areas. The purpose of this study was to estimate the soil heavy metal concentrations based on Gaofen 5 (GF5) satellite hyperspectral imagery for the assessment of the heavy metal pollution in the study area and to analyze the scale effect under different resolutions. A total of 96 topsoil samples were collected in this work, and these samples were analyzed for the arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn) contents. To solve the problem of the insignificant features caused by the complex imaging conditions of spaceborne hyperspectral satellite imagery, the binary weight symbiotic organisms search algorithm (BWSOS) was developed. After feature selection based on the BWSOS method, the heavy metal contents are inverted by the use of support vector machine regression. The experimental results show that the BWSOS feature selection method shows a good performance, with the R-p(2) values for As, Cd, Cr, Cu, Ni, Pb, and Zn being 0.67, 0.68, 0.73, 0.71, 0.66, 0.65, and 0.71, respectively. Based on the estimated heavy metal concentration maps, the geoaccumulation index (I-geo), the pollution index, and the potential ecological risk index were calculated to assess the heavy metal pollution status in the study area. The results showed that only As contamination is present at a significant level, but with a low level of potential risk for the whole study area. A comparison with the results obtained using HyMap airborne hyperspectral imagery showed that the GF5 satellite hyperspectral imagery can obtain consistent results for heavy metal pollution assessment. The airborne hyperspectral imagery can provide more fine details, whereas the spaceborne hyperspectral imagery is more suitable for large-scale pollution assessme

关键词： hyperspectral imagery symbiotic organisms search soil heavy metal estimation heavy metal pollution pollution index scale effect

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Biological characteristics of energy conversion in carbon fixation by microalgae

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RENEWABLE & SUSTAINABLE ENERGY REVIEWS 2021年 152卷

作者： Zeng, Jing Wang, Zhenjun Chen, Guobin Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing 211106 Peoples R China Univ Shanghai Sci & Technol Coll Mech Engn Shanghai 200093 Peoples R China Chongqing Technol & Business Univ Rongzhi Coll Chongqing Key Lab Spatial Data Min & Big Data Int Chongqing 401320 Peoples R China

CO2-fixation by microalgae can be regarded as a biological process of energy conversion with CO2 and H2O in microalgae cells in the sunlight. The study of the biological intrinsic characteristics of energy conversion is helpful to reveal the high-efficiency carbon fixation mechanism of microalgae. Firstly, the CO2 emission control technology and the external influencing factors are summarized in this paper, which have laid the foundation for researching the internal biological intrinsic characteristics of carbon fixation by microalgae. Based on photosynthetic reactions, in-situ reaction experiments, hydrodynamic simulations and metabolic networks have been integrated to analyze the biological intrinsic characteristics of carbon fixation by microalgae. The collation of representative studies on theory and quantitative calculation methods reveals that free energy dissipation seriously affects the carbon fixation efficiency of microalgae;Secondly, thermodynamics and metabolic networks are discussed. The role of thermodynamics in addressing the constraints is explored mainly from the perspective of energy conversion mechanisms, free energy dissipation mechanisms, framework and methods. Metabolic networks are studied using sampling methods based on thermodynamic systems and metabolic engineering based on a systems perspective;Thirdly, the key supporting technologies and biological intrinsic characteristics are reviewed from an interdisciplinary perspective, and the researches on metabolic networks based on thermodynamic constraints are given;Finally, challenges are summarized to provide a basis and direction for future research.

关键词： Microalgae Carbon fixation Photosynthetic reaction Carbon pump Energy conversion

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bigNN: Bipartite graph neural network with attention mechanism for solving multiple traveling salesman problems in urban logistics

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intERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION 2024年 129卷

作者： Liang, Haojian Wang, Shaohua Li, Huilai Zhou, Liang Zhang, Xueyan Wang, Shaowen Chinese Acad Sci Aerosp Informat Res Inst Key Lab Remote Sensing & Digital Earth Beijing 100094 Peoples R China Jilin Univ Sch Artificial Intelligence Changchun 130012 Peoples R China Int Res Ctr Big Data Sustainable Dev Goals Beijing 100094 Peoples R China Jilin Univ Sch Math Changchun 130012 Peoples R China Lanzhou Jiaotong Univ Fac Geomat Lanzhou 730070 Peoples R China Univ Southern Calif Viterbi Sch Engn Los Angeles CA 90089 USA Univ Illinois CyberGIS Ctr Adv Digital & Spatial Studies 1301 W Green St Urbana IL 61801 USA

The multiple traveling salesman problems (MTSP), which arise from real world problems, are essential in urban logistics. Variations such as minMax-MTSP and Bounded-MTSP aim to distribute workload evenly among salesmen and impose constraints on visited cities, respectively. Branch-and-bound (B&B) provides an exact algorithm solution for these problems. The Learn to Branch (L2B) approach guides branch node selection through deep learning. In this study, we utilize mathematical modeling of Bipartite Graph Neural Network (bigNN) and an attention mechanism to support B&B in exploring solution spaces through imitation learning. The problems are framed to formulate mixed integer linear programming, which is different from conventional algorithms. It is proposed that a bipartite graph network approach makes a feature representation by setting a structure of constraints and variables. Experimental results showed that our model can generate more accurate solutions than three benchmark models. The bigNN model can effectively learn the strong branch strategy, which reduces solution time by replacing complex calculations with fast approximations. Additionally, the small-scale instances model can be applied to larger-scale ones.

关键词： Bipartite graph Graph neural network Attention mechanism Multiple traveling salesman problem Branch-and-bound

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Reversing net loss but aggravating fragmentation of habitat in the global Asian elephant range in the mid-2010s

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BIOLOGICAL CONSERVATION 2025年 307卷

作者： Zhang, Xin Campos-Arceiz, Ahimsa Chen, Fei Yin, Wenping Xie, Fei Zhang, Jiejing Fan, Hui Yunnan Univ Inst Int Rivers & Ecosecur Kunming 650500 Yunnan Peoples R China Yunnan Univ Yunnan Key Lab Int Rivers & Transboundary Ecosecur Kunming 650500 Yunnan Peoples R China Minist Educ Key Lab Ecosecur Southwest China Kunming 650500 Yunnan Peoples R China Chinese Acad Sci Southeast Asia Biodivers Res Inst Mengla 666303 Yunnan Peoples R China Chinese Acad Sci Ctr Integrat Conservat Xishuangbanna Trop Bot Garden Mengla 666303 Yunnan Peoples R China Yunnan Int Joint Lab Southeast Asia Biodivers Cons Mengla 666303 Yunnan Peoples R China Yunnan Key Lab Conservat Trop Rainforests & Asian Mengla 666303 Yunnan Peoples R China Asian Elephant Res Ctr Natl Forestry & Grassland A Kunming 650216 Yunnan Peoples R China China Univ Min & Technol Sch Environm & Spatial Informat Xuzhou 221116 Jiangsu Peoples R China Tech Univ Munich Professorship Big Geospatial Data Management D-85521 Ottobrunn Germany

Megafauna, such as elephants, are flagship species and play keystone roles in maintaining ecosystem function. Human-induced deforestation has considerably reduced the global geographic range and population size of Asian elephants (Elephas maximus) in recent decades, yet some reports suggest a possible recent recovery of some of their habitats. The long-term global dynamics of these habitats, however, remain largely unknown. In this study, we compiled environmental covariates from 39 published papers that assessed habitat suitability for Asian elephants. Using these covariates and a habitat suitability index model, we investigated the interannual dynamics of habitat suitability across the species' range from 2000 to 2020. Additionally, we analyzed trends in habitat fragmentation during the same period. Our findings revealed a significant 4.36 % decline in suitable habitat areas over two decades. interestingly, a tipping point occurred around 2014, when habitat suitability stabilized and began to show slight improvement. However, habitat fragmentation continued to worsen throughout the study period. Notably, habitat suitability was higher in transboundary regions, where degradation was less severe than within protected areas. After 2018, habitat suitability in transboundary regions surpassed that of the protected areas. These findings emphasize the need to prioritize the protection of remaining Asian elephant populations and address the challenges of habitat fragmentation and connectivity across the species' range. Our study highlights the conservation potential often-overlooked transboundary regions and underscores the importance of leveraging geospatial data spanning long time periods and large spatial scales for comprehensive habitat evaluations.

关键词： Fragmentation Habitat evaluation Habitat loss and degradation Landscape metrics Time series analysis Transboundary conservation

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Identifying lithofacies types by boosting algorithm and resampling technique: a case study of deep-water submarine fans in an oil field in West Africa

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PETROLEUM SCIENCE AND TECHNOLOGY 2024年第25期42卷 4192-4215页

作者： Zhen, Yan Xiao, Yifei Zhao, Xiaoming Lu, Xiaoya Fang, Junyi Kang, Jintao Liu, Liang Southwest Petr Univ Sch Geosci & Technol Chengdu Sichuan Peoples R China Southwest Petr Univ Nat Gas Geol Key Lab Sichuan Prov Chengdu Sichuan Peoples R China Spatial Informat Technol & Big Data Min Res Ctr Chengdu Sichuan Peoples R China Southwest Minzu Univ Sch Comp Sci & Technol Chengdu Sichuan Peoples R China

The continuous discovery of giant oil and gas fields in deep-water low stand fans has made deep-water submarine fan reservoirs with huge oil and gas potential important targets for oil and gas exploration and development. Nowadays, machine learning algorithm has been proven to be an effective method to classify various rock types from geophysical logging data, but rarely has there been focus on predicting deep-water submarine fans in previous studies. In this paper, we utilized five classical Boosting machine learning algorithms, namely GBDT, XGBoost, LightGBM, CatBoost, and LogitBoost, to identify 14 deep-water submarine fan lithofacies types from 7 wells in a West African oilfield. To address the sample non-balance problem, we employed SMOTE and MAHAKIL oversampling techniques and optimized the hyperparameters of the model using Genetic Algorithm. The experimental results show that the model performance is improved by using oversampling technologies and hyperparameter optimization. The proposed MAHAKIL-GA-GBDT algorithm is the most effective in identifying the lithofacies of deep-water submarine fans, with an accuracy of 0.986. This study provides a new approach for identifying deep-water submarine fan lithofacies and highlights the potential of machine learning algorithms in this field.

关键词： Boosting deep-water submarine fans genetic algorithm lithofacies identification machine learning oversampling

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Targeting mitochondrial DNA-STING-NF-κB Axis-mediated microglia activation by cryptotanshinone alleviates ischemic retinopathy

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PHYTOMEDICINE 2025年 142卷

作者： Qiu, Wanlu Zheng, Zhihua Wang, Jiaojiao Cai, Youran Zou, Jiami Huang, Ziqing Yang, Pinglian Ye, Weile Jin, Mei Zhang, Dongmei Little, Peter J. Zhou, Qing Liu, Zhiping Jinan Univ State Key Lab Bioact Mol & Druggabil Assessment Guangdong Prov Key Lab Pharmacodynam Constituents Coll PharmMinist Educ MOEInt Cooperat Lab Tradit Guangzhou 510632 Peoples R China Jinan Univ Affiliated Hosp 1 Dept Ophthalmol Guangzhou 510006 Peoples R China Jinan Univ Affiliated Guangdong Second Prov Gen Hosp Sch Pharm Postdoctoral Res Stn Tradit Chinese Med Guangzhou 510632 Peoples R China Guangdong Med Univ Lab Comp Aided Drug Design Dongguan City Key Lab Big Data Min & Precis Drug Design Sch PharmKey Lab Res & Dev Nat Drugs Guangdong Pr Dongguan 523808 Peoples R China Univ Queensland Pharm Australia Ctr Excellence Sch Pharm Woolloongabba Qld 4102 Australia Guangzhou Xinhua Univ Dept Pharm Guangzhou 510520 Peoples R China

Background: Ischemic retinopathy, a leading cause of vision impairment, involves oxidative stress and dysregulated inflammation, with microglia playing a key role. Cryptotanshinone (CTS), a bioactive compound from Salvia miltiorrhiza, exhibits anti-inflammatory and antioxidant properties and thus has the potential for development as a therapeutic agent. However, the actual mechanism of action of CTS in ischemic retinopathy is not known. Overactivation of the STING pathway in microglia is critical in ischemic retinopathy pathogenesis and a potential target of CTS. Purpose: This study aimed to explore whether CTS alleviates ischemic retinopathy by modulating microglial STING signaling. Methods: Oxygen-induced retinopathy (OIR) mice and hypoxia-induced microglial cells were used. CTS efficacy in ischemic retinopathy was evaluated at multiple stages using fluorescein fundus angiography, electroretinogram, H&E staining, and Western blotting of relevant proteins. Network pharmacology and RNA sequencing identified STING as a key target. Furthermore, surface plasmon resonance (SPR), molecular docking, and sitedirected mutagenesis were systematically employed to elucidate the precise binding interface between CTS and the STING protein. STING activation and knockout models were employed to further investigate the mechanisms of action of CTS. Results: CTS treatment reduced microglial activation and pathological retinal angiogenesis, and protected both retinal function and structure in OIR mice. Network pharmacology, RNA sequencing, and experimental validation demonstrated a significant link between the protective effect of CTS and the inhibition of STING signaling. Mechanistically, CTS suppressed cytosolic mtDNA release, blocked STING translocation from the ER to the Golgi, and enhanced lysosomal STING degradation. These CTS-mediated effects were abolished by STING activation and absent in Sting-deficient OIR mice. Notably, CTS combined with anti-VEGF therapy showed synergisti

关键词： Ischemic retinopathy Cryptotanshinone mtDNA STING Microglia

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Link prediction in multilayer networks using weighted reliable local random walk algorithm

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EXPERT SYSTEMS WITH APPLICATIONS 2024年 247卷

作者： Luo, Zhiping Yin, Jian Lu, Guangquan Rahimi, Mohammad Reza Sun Yat Sen Univ Guangdong Key Lab Big Data Anal & Proc Guangzhou 510006 Guangdong Peoples R China Yunnan Minzu Univ Lancang Mekong Int Vocat Inst Kunming 650005 Yunnan Peoples R China Guangxi Normal Univ Guangxi Key Lab Multisource Informat Min & Secur Guilin 541004 Guangxi Peoples R China Qeshm Inst Higher Educ Software Engn Qeshm Iran

The expansion of online social networks has led to attracting a significant number of users. Meanwhile, the analysis of these networks has raised new perspectives and challenges due to the large amount of information. One of these challenges in the analysis of social networks is the problem of link prediction. The purpose of this problem is to find links that have not yet been observed, but may exist in the future. There are many solutions for link prediction on monoplex networks. However, many real social networks model communication in multiple layers. In recent years, link prediction in multilayer social networks has attracted the attention of many researchers. A solution for multilayer networks involves taking into account the information of all layers to make predictions for a target layer. Among the link prediction techniques based on monoplex networks, local random walk is very popular. This paper presents an extended version of this technique for multilayer social networks considering reliable routes and weighted links. Our proposed algorithm as Weighted Reliable Local Random Walk (WRLRW) simultaneously uses interlayer and intralayer information to predict links in a target layer of a multilayer network. WRLRW adjusts link weights based on multimodal and topological features and forms reliable routes between users by multiplying link weights. We demonstrated the effectiveness of WRLRW to address the link prediction problem on real-world multilayer networks through numerical simulations. WRLRW has better performance compared to link prediction techniques based on monoplex networks as well as state-ofthe-art methods based on multilayer networks. According to the results of the experiments, WRLRW obtains 3.2% and 2.5% better average f-measure compared to SEM-Path (Structural, Ego-Paths and Meta-Paths features) and MLRW (Multiplex Local Random Walk), respectively.

关键词： Link prediction Local random walk Multilayer networks Reliable routes Weighted links Social networks

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