Multiple Types of Missing Precipitation Data Filling Based on Ensemble Artificial Intelligence Models DOI Open Access
Qiu He, Hao Chen,

Bingjiao Xu

et al.

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3192 - 3192

Published: Nov. 7, 2024

The completeness of precipitation observation data is a crucial foundation for hydrological simulation, water resource analysis, and environmental assessment. Traditional imputation methods suffer from poor adaptability, lack precision, limited model diversity. Rapid accurate using available key challenge in monitoring. This study selected the Jiaojiang River basin southeastern Zhejiang Province China 1991 to 2020. were categorized based on various missing rates scenarios, namely MCR (Missing Completely Random), MR MNR Not Random). Imputation was conducted three types Artificial Intelligence (AI) (Backpropagation Neural Network (BPNN), Random Forest (RF), Support Vector Regression (SVR)), along with novel Multiple Linear (MLR) method built upon these algorithms. results indicate that constructed MLR achieves an average Pearson’s correlation coefficient (PCC) 0.9455, Nash–Sutcliffe Efficiency (NSE) 0.8329, Percent Bias (Pbias) 10.5043% across different rates. simulation higher NSE lower Pbias than other single AI models, thus effectively improving estimation performance. proposed this can be applied river basins improve quality support management.

Language: Английский

Elektrokoagülasyon yöntemiyle atık sularının arıtımı: etkinlik, modelleme ve kontrol yaklaşımları DOI Open Access

Dursun Alp Kizilöz,

Metin Demirtaş

Balıkesir Üniversitesi Fen Bilimleri Enstitüsü Dergisi, Journal Year: 2025, Volume and Issue: 27(2), P. 425 - 442

Published: March 22, 2025

Elektrokoagülasyon, atık suya daldırılmış anot ve katot metallerine elektrik akımı uygulanarak kirleticilerin elektrokimyasal reaksiyonlarla giderilmesini sağlayan bir arıtma yöntemidir. Geleneksel yöntemlere kıyasla daha düşük enerji tüketimi, az kimyasal kullanımı kısa işlem süresi gibi avantajlarıyla öne çıkar. Ancak, bu prosesin etkinliği; akım yoğunluğu, elektrot tipi, bağlantı konfigürasyonu, pH sıcaklık birçok faktöre bağlıdır. Bu çalışmada, tekstil kağıt endüstrisi başta olmak üzere farklı sularda gerçekleştirilen elektrokoagülasyon çalışmaları gözden geçirilmiş, parametrelerin süreci üzerindeki etkileri ayrıntılı şekilde incelenmiştir. Araştırmalar hem de endüstrisinde prosesi sonucunda %90’ın üzerinde Kimyasal Oksijen İhtiyacı (KOİ) giderim veriminin elde edilebileceğini göstermektedir. Farklı sular yapılan modelleme kontrol sonucunda, optimizasyon uygulamalarıyla, veriminde artış maliyetinde azalma sağlandığı tespit edilmiştir. makalede, prosesinin temel çalışma prensipleri, proses etkili olan faktörler iyileştirmeye yönelik ile kapsamlı analiz

Citations

0
Innovative approaches to greywater micropollutant removal: AI-driven solutions and future outlook DOI Creative Commons
Mohamed Mustafa,

Emmanuel I. Epelle,

Andrew Macfarlane

et al.

RSC Advances, Journal Year: 2025, Volume and Issue: 15(16), P. 12125 - 12151

Published: Jan. 1, 2025

Greywater constitutes a significant portion of urban wastewater and is laden with numerous emerging contaminants that have the potential to adversely impact public health ecosystem.

Language: Английский

Citations

0
Recent progress in highly effective electrocoagulation-coupled systems for advanced wastewater treatment DOI Creative Commons
Thi Kim Cuong Phu, Phi Long Nguyen, Thi Viet Bac Phung

et al.

iScience, Journal Year: 2025, Volume and Issue: 28(3), P. 111965 - 111965

Published: Feb. 7, 2025

Electrocoagulation (EC) has been a well-known technology for wastewater treatment over the past centuries, owing to its straightforward equipment requirements and highly effective contaminant removal efficiency. This literature review emphasizes influence of several input variables in EC system such as electrode materials, applied current, pH, supporting electrolyte, inner-electrode distance on effluent efficiency energy consumption. Besides that, depending intrinsic properties effluents, is recommended hybridize with other methods physical-, biological-, chemical-, electrochemical order enhance performance reduce Subsequently, comprehensive analysis presented, including power consumption, evaluation synergistic effect multiple using statistical methods. Finally, this discusses future perspectives environmentally friendly utilization post-EC treated sludges, development renewable energy-driven systems, challenges management by artificial intelligence.

Language: Английский

Citations

0
The performance of electrocoagulation process for decolorization and COD removal of highly colored real grey water under variable operating conditions DOI Creative Commons

Muhammad Rasool Al-Kilan,

Khalid Bani‐Melhem

Desalination and Water Treatment, Journal Year: 2024, Volume and Issue: unknown, P. 100924 - 100924

Published: Nov. 1, 2024

Language: Английский

Citations

1
Hybrid Electrocoagulation–Adsorption Process for Montelukast Sodium Antibiotic Removal from Water DOI Creative Commons

Sayedali Mirkhalafi,

Khalid Hashim, Osamah Al-Hashimi

et al.

Clean Technologies, Journal Year: 2024, Volume and Issue: 6(4), P. 1537 - 1564

Published: Nov. 20, 2024

This study addresses the significant environmental challenge of pharmaceutical pollutants by demonstrating effectiveness a hybrid electrocoagulation–adsorption (EC-A) technique for removing Montelukast Sodium (MS) from contaminated water. The research was conducted in three stages—adsorption, electrocoagulation, and adsorption using residual water electrocoagulation process. adsorbent materials were characterised various analytical techniques: X-ray Diffraction (XRD) determining crystalline structure, Energy-Dispersive Spectroscopy (EDX) elemental composition, Scanning Electron Microscopy (SEM) surface morphology, Fourier Transform Infrared (FTIR) identifying functional groups before after interaction with pollutants. phase achieved optimal results at pH 3 contact time 120 min, maximum removal efficiency 99.5% starting MS concentration 50 mg/L Calcium Ferric Oxide–Silica Sand (CFO-SS) adsorbent. showed 97% 11, current density 20 mA, 5 mm electrode distance, just min. Finally, combined EC-A process, adjusted to 3, further enhanced 74%, highlighting method’s potential contaminant removal. These findings underscore as highly effective adaptable solution mitigating contaminants

Language: Английский

Citations

1
Mechanisms of data mining in analyzing the effects and trends of news dissemination DOI Creative Commons
Lihong Zhang

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract Data mining techniques can help news organizations and media practitioners extract valuable information from a large amount of unorganized information, such as by analyzing the effect dissemination. In data mining, multiple linear regression is widely used technical model. this paper, we utilize classic “cognition-attitude-behavior” analysis framework to construct model communication effect. We solve positional parameters according principle least squares, ensuring that value all observations have minimum residual square. then system equations using Clem’s law Gaussian elimination method. The constructed models are analyze dissemination Guangzhou’s city image on traditional platforms microblog self-media platforms, respectively. It found videos “cultural image” “ecological significant positive longer duration video, better terms influence event-related online opinion leaders dissemination, number comments likes influence, with coefficients 0.778 0.059, respectively, both at 1% level. addition likes, influencing factors related fans, whether there V authentication, microblogging membership. After conducting two empirical analyses, verified validity in paper trend

Language: Английский

Citations

0
Covalent organic frameworks (COFs) and COFs-based hybrid architectonics: A promising material platform for organic micropollutants detection and removal from wastewater DOI
Lalit Goswami, Anamika Kushwaha,

Mohd Shabbir

et al.

Coordination Chemistry Reviews, Journal Year: 2024, Volume and Issue: 527, P. 216398 - 216398

Published: Dec. 22, 2024

Language: Английский

Citations

0
Multiple Types of Missing Precipitation Data Filling Based on Ensemble Artificial Intelligence Models DOI Open Access
Qiu He, Hao Chen,

Bingjiao Xu

et al.

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3192 - 3192

Published: Nov. 7, 2024

The completeness of precipitation observation data is a crucial foundation for hydrological simulation, water resource analysis, and environmental assessment. Traditional imputation methods suffer from poor adaptability, lack precision, limited model diversity. Rapid accurate using available key challenge in monitoring. This study selected the Jiaojiang River basin southeastern Zhejiang Province China 1991 to 2020. were categorized based on various missing rates scenarios, namely MCR (Missing Completely Random), MR MNR Not Random). Imputation was conducted three types Artificial Intelligence (AI) (Backpropagation Neural Network (BPNN), Random Forest (RF), Support Vector Regression (SVR)), along with novel Multiple Linear (MLR) method built upon these algorithms. results indicate that constructed MLR achieves an average Pearson’s correlation coefficient (PCC) 0.9455, Nash–Sutcliffe Efficiency (NSE) 0.8329, Percent Bias (Pbias) 10.5043% across different rates. simulation higher NSE lower Pbias than other single AI models, thus effectively improving estimation performance. proposed this can be applied river basins improve quality support management.

Language: Английский

Citations

0