Prediction of summer precipitation via machine learning with key climate variables：A case study in Xinjiang, China DOI Creative Commons

Chenzhi Ma,

Junqiang Yao,

Yinxue Mo

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 101964 - 101964

Опубликована: Сен. 16, 2024

Язык: Английский

Prediction of Summer Precipitation Via Machine Learning with Key Climate Variables:A Case Study in Xinjiang, China DOI

Chenzhi Ma,

Junqiang Yao,

Yinxue Mo

и другие.

Опубликована: Янв. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Язык: Английский

Процитировано

1
Schedule-cost optimization in high-rise buildings considering uncertainty DOI
Jinting Huang, Ankang Ji, Zhonghua Xiao

и другие.

Engineering Construction & Architectural Management, Год журнала: 2024, Номер unknown

Опубликована: Июнь 18, 2024

Purpose The paper aims to develop a useful tool that can reliably and accurately find the critical paths of high-rise buildings provide optimal solutions considering uncertainty based on Monte Carlo simulation (MCS) enhance project implementation performance by assisting site workers managers in building engineering. Design/methodology/approach This research proposes an approach integrating improved nondominated sorting genetic algorithm II (NSGA-II) delay scenarios simulated MCS with technique for order preference similarity ideal solution. Findings results demonstrate proposed is capable generating solutions, which improve construction guide management shortening engineering schedule cost under conditions. Research limitations/implications In this study, only data two floors was focused due at stage, future work analyze whole stage examine approach, multi-objective optimization (MOO) considered factors as objectives, where more such schedule, quality, be expanded future. Practical implications successfully applied process buildings, guidance basis optimizing construction. Originality/value innovations advantages derived from underline its capability handle scheduling (CSO) problems different objectives

Язык: Английский

Процитировано

1
Feature Importance in Machine Learning with Explainable Artificial Intelligence (XAI) for Rainfall Prediction DOI Creative Commons
Mehul Patel, Ankit Shah

ITM Web of Conferences, Год журнала: 2024, Номер 65, С. 03007 - 03007

Опубликована: Янв. 1, 2024

Precipitation expectation is a pivotal subject for the administration of water assets and counteraction hydrological calamities. To make precipitation forecast find essential elements influencing precipitation, this study presents logical profound learning approach in two sections. The initial segment with consideration system which could foresee while second part clarification figures attribution values information weather conditions to evaluate their significance. A contextual investigation led on hourly India’s population wise top eight urban cities. outcomes predominantly demonstrate that main whose component esteem adversely/decidedly corresponded its esteem. review’s importance lies upgrading giving interpretability through recognizable proof persuasive variables, works long haul arranging more comprehension mind-boggling climate frameworks.

Язык: Английский

Процитировано

1
Flood prediction through hydrological modeling of rainfall using Conv1D-SBiGRU algorithm and RDI estimation: A hybrid approach DOI

G. Selva Jeba,

P. Chitra

Stochastic Environmental Research and Risk Assessment, Год журнала: 2024, Номер 38(9), С. 3587 - 3606

Опубликована: Июль 20, 2024

Язык: Английский

Процитировано

1
Prediction of summer precipitation via machine learning with key climate variables：A case study in Xinjiang, China DOI Creative Commons

Chenzhi Ma,

Junqiang Yao,

Yinxue Mo

и другие.

Journal of Hydrology Regional Studies, Год журнала: 2024, Номер 56, С. 101964 - 101964

Опубликована: Сен. 16, 2024

Язык: Английский

Процитировано

1