An All-Hazards Return on Investment (ROI) Model to Evaluate U.S. Army Installation Resilient Strategies

Systems, Год журнала: 2025, Номер 13(2), С. 90 - 90

Опубликована: Янв. 31, 2025

The paper describes our project to develop, verify, and deploy an All-Hazards Return of Investment (ROI) model for the U. S. Army Engineer Research Development Center (ERDC) provide army installations with a decision support tool evaluating strategies make existing installation facilities more resilient. need increased resilience extreme weather caused by climate change was required U.S. code DoD guidance, as well strategic plan that stipulated ROI evaluate relevant resilient strategies. During project, ERDC integrated University Arkansas designed into new planning expanded scope options from all hazards. Our methodology included research on policy, data sources, options, analytical techniques, along stakeholder interviews weekly meetings developers. uses standard risk analysis engineering economics terms analyzes potential hazards using in tool. calculates expected net present cost without strategy, each strategy. minimum viable product formulated mathematically, coded Python, verified hazard scenarios, provided implementation.

Язык: Английский

---

Prediction of PM_2.5 and CO₂ concentrations using the PCA-LightGBM method in Bandung, Indonesia

Journal of Physics Conference Series, Год журнала: 2025, Номер 2942(1), С. 012004 - 012004

Опубликована: Фев. 1, 2025

Abstract Poor air quality due to large amounts of human activity shows the need increase public awareness and alertness by building a system predicting future pollutant concentrations. This research creates prediction using LightGBM algorithm for PM 2.5 CO 2 parameters with an additional parameter reduction method PCA accuracy. The number valid datasets is 918 each five at measurement station, data gaps filled median values so that they can be used predictions. results show best accuracy Deli which uses MAPE 21.5%, , it achieved station without 4.8%. Based on its accuracy, less suitable if there are outliers in dataset, but ideal homogeneous datasets. Overall, based feasible category, accurate very category. To optimize results, especially long term, necessary retrain complete up-to-date dataset better suit conditions.

Язык: Английский

---

Spatiotemporal Differentiation and Driving Factors of Urban–Rural Integration in Counties of Yangtze River Economic Belt

Land, Год журнала: 2025, Номер 14(4), С. 889 - 889

Опубликована: Апрель 17, 2025

Assessing URI and its driving mechanisms can promote urban–rural integration (URI). However, existing research has often underexplored county-scale analyses within national strategic zones in China given limited attention to the spatiotemporal impacts of drivers. Focusing on Yangtze River Economic Belt (YREB) China, this study examined dynamics county-level from 2000 2020 analyzed heterogeneity effects drivers using a geo-detector geographically temporally weighted regression (GTWR) model. The findings reveal following: (1) level counties YREB generally increased over period, though social spatial lagged behind economic environmental integration. (2) decreased spatially east west, forming high low levels agglomeration YREB’s urban agglomerations provincial fringes respectively. (3) development, fixed asset investment, transportation accessibility, geographical conditions drove differentiation counties. elevation significantly hindered eastern region, while central region was promoted by investment despite inhibitory effect slope. In western development played critical facilitating role, but slope remained limiting factor. Tailored strategies are needed for different regions URI.

Язык: Английский

---

The Influence of Passenger Car Banning Policies on Modal Shifts: Rotterdam’s Case Study

Sustainability, Год журнала: 2023, Номер 15(9), С. 7443 - 7443

Опубликована: Апрель 30, 2023

Low-emission zones (LEZs), incentivizing electric cars, park-and-ride systems, and other traffic reduction schemes, are all single measures aimed at achieving low-/zero-emission mobility. This paper aims to investigate the impact of LEZs’ passenger car banning argues that such cannot achieve significant or emission levels without being integrated into a well-designed policy package ensures sufficient provision mobility alternatives. Featuring Rotterdam as case study, this follows mixed methodology consisting (1) quantitative real-time data on transport usage mirror users’ behavior (2) qualitative acquired from in-depth interviews documents explain government’s intention behavior. The results show between 2016 2020, after applying LEZ for restricting cars vans Euro 3 lower, there was 50% decrease in number polluting entering Rotterdam. However, is insignificant, since vehicles targeted by less than 2% overall entered area. also shed light role systematic packaging ensuring change user Among initiatives, successful implantation should be supported inner-city parking reduction, vehicle charging facilities, incentive alternative sustainable options. Above all, restricted must significant. conclusion discussion develop well-structured, educational, evaluative framework recommend comprehensive cities seeking low-emission research, however, did not consider different land-use distributions application LEZ, which can an interesting angle future researchers.

Язык: Английский

---

Students learning performance prediction based on feature extraction algorithm and attention-based bidirectional gated recurrent unit network

PLoS ONE, Год журнала: 2023, Номер 18(10), С. e0286156 - e0286156

Опубликована: Окт. 25, 2023

With the development of information technology construction in schools, predicting student grades has become a hot area application current educational research. Using data mining to analyze influencing factors students' performance and predict their can help students identify shortcomings, optimize teachers' teaching methods enable parents guide children's progress. However, there are no models that achieve satisfactory predictions for education-related public datasets, most these weakly correlated datasets still adversely affect predictive effect model. To solve this issue provide effective policy recommendations modernization education, paper seeks find best grade prediction model based on mining. Firstly, study uses Factor Analyze (FA) extract features from original dimension reduction. Then, Bidirectional Gate Recurrent Unit (BiGRU) attention mechanism utilized grades. Lastly, Comparing results ablation experiments other single models, such as linear regression (LR), back propagation neural network (BP), random forest (RF), (GRU), FA-BiGRU-attention achieves performs equally well different multi-step predictions. Previously, problems with were only detected when they had already appeared. presented learning advance identification affecting Therefore, great potential support improvement programs, transform traditional education industry, ensure sustainable national talents.

Язык: Английский

---