日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Towards intelligent air quality forecasting using integrated machine learning framework with variational mode decomposition and catboost feature selection

基于集成机器学习框架、变分模态分解和CatBoost特征选择的智能空气质量预测

Ahmadianfar, Iman; Yaseen, Zaher Mundher; Marhoon, Haydar Abdulameer; Halder, Bijay; Tan, Mou Leong; Kilinc, Huseyin Cagan; Abba, Sani I; Heddam, Salim; Goliatt, Leonardo; Demir, Vahdettin; Al-Areeq, Ahmed M

Accurate and interpretable prediction of chemical oxygen demand using explainable boosting algorithms with SHAP analysis

利用可解释的增强算法和SHAP分析,对化学需氧量进行准确且可解释的预测。

Merabet, Khaled; Kim, Sungwon; Heddam, Salim; Di Nunno, Fabio; Granata, Francesco; Kisi, Ozgur; Adnan, Rana Muhammad; Zounemat-Kermani, Mohammad; Külls, Christoph

Integration of Gaussian process regression and K means clustering for enhanced short term rainfall runoff modeling

将高斯过程回归和K均值聚类相结合,以增强短期降雨径流模型的建模能力。

Kisi, Ozgur; Heddam, Salim; Parmar, Kulwinder Singh; Petroselli, Andrea; Külls, Christoph; Zounemat-Kermani, Mohammad

Air temperature estimation and modeling using data driven techniques based on best subset regression model in Egypt

埃及基于最佳子集回归模型的数据驱动技术气温估算和建模

Elbeltagi, Ahmed; Vishwakarma, Dinesh Kumar; Katipoğlu, Okan Mert; Sushanth, Kallem; Heddam, Salim; Singh, Bhaskar Pratap; Shukla, Abhishek; Gautam, Vinay Kumar; Pande, Chaitanya Baliram; Hussain, Saddam; Ghosh, Subhankar; Dehghanisanij, Hossein; Salem, Ali

The development of an efficient artificial intelligence-based classification approach for colorectal cancer response to radiochemotherapy: deep learning vs. machine learning

开发一种高效的基于人工智能的结直肠癌放化疗反应分类方法:深度学习与机器学习

Bahrambanan, Fatemeh; Alizamir, Meysam; Moradveisi, Kayhan; Heddam, Salim; Kim, Sungwon; Kim, Seunghyun; Soleimani, Meysam; Afshar, Saeid; Taherkhani, Amir

Development of the machine learning and deep learning models with SHAP strategy for predicting groundwater levels in South Korea

利用SHAP策略开发机器学习和深度学习模型,用于预测韩国地下水位

Kim, Sungwon; Alizamir, Meysam; Heddam, Salim; Chang, Sun Woo; Chung, Il-Moon; Kisi, Ozgur; Kulls, Christoph

Daily river flow simulation using ensemble disjoint aggregating M5-Prime model

利用集合不相交聚合M5-Prime模型进行日河流流量模拟

Khosravi, Khabat; Attar, Nasrin; Bateni, Sayed M; Jun, Changhyun; Kim, Dongkyun; Safari, Mir Jafar Sadegh; Heddam, Salim; Farooque, Aitazaz; Abolfathi, Soroush

Development of a robust daily soil temperature estimation in semi-arid continental climate using meteorological predictors based on computational intelligent paradigms

基于计算智能范式的气象预测因子在半干旱大陆性气候下开发稳健的日土壤温度估算方法

Alizamir, Meysam; Ahmed, Kaywan Othman; Kim, Sungwon; Heddam, Salim; Gorgij, AliReza Docheshmeh; Chang, Sun Woo

Pre- and post-dam river water temperature alteration prediction using advanced machine learning models

利用先进的机器学习模型预测大坝建成前后河流水温变化

Vishwakarma, Dinesh Kumar; Ali, Rawshan; Bhat, Shakeel Ahmad; Elbeltagi, Ahmed; Kushwaha, Nand Lal; Kumar, Rohitashw; Rajput, Jitendra; Heddam, Salim; Kuriqi, Alban

Assessing the performance of a suite of machine learning models for daily river water temperature prediction

评估一系列机器学习模型在每日河流水温预测方面的性能

Zhu, Senlin; Nyarko, Emmanuel Karlo; Hadzima-Nyarko, Marijana; Heddam, Salim; Wu, Shiqiang