Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China

Zhang, Lei; Zou, Zhihong; Shan, Wei

doi:10.1016/j.jes.2016.07.017

Cited by 44 publications

(29 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The weight value [27] of each indicator is determined, and the specific values are constructed, referring to the 1-9 scale method proposed by Saaty for the judgment matrix. If the parameter on the horizontal axis is less important than the parameter on the vertical axis, it carries a value between 1 and 9.…”

Section: Assessment Weight Setsmentioning

confidence: 99%

An Occupational Disease Assessment of the Mining Industry’s Occupational Health and Safety Management System Based on FMEA and an Improved AHP Model

2017

View full text Add to dashboard Cite

Abstract:In order to effectively analyze, control, and prevent occupational health risk and ensure the reliability of the weight, a method based on FMEA (failure mode and effects analysis) and an improved AHP (analytic hierarchy process) model was established. The occupational disease of the occupational health and safety management system (OHSAS18001) of the mining industry in the southwest of Hubei Province is taken as an example, the three most significant risk factors (dust, noise, and gas) are selected as the research objects, the FMEA method is used, an expert questionnaire is carried out to establish the comprehensive assessment matrix of each indicator according to the RPN (risk priority number) value, and, finally, a case study is conducted through the FMEA and the improved AHP model The results show that the occupational disease of the mining industry's occupational health and safety management system belongs to a "general" grade, which is in line with the physical examination results of the Center for Disease Control and Prevention of Ezhou City in 2015. The improved AHP and FMEA comprehensive assessment model of occupational disease is proved feasible. This method can be incorporated in the process management of the enterprise for the purpose of occupational disease prevention in advance and continuous improvement on the occupational health and safety of employees. Additionally, the area research on this integrated model should be optimized continually in actual situations.

show abstract

Section: Assessment Weight Setsmentioning

confidence: 99%

An Occupational Disease Assessment of the Mining Industry’s Occupational Health and Safety Management System Based on FMEA and an Improved AHP Model

2017

View full text Add to dashboard Cite

show abstract

“…In their method, dissolved oxygen, chemical oxygen demand by KMnO4 and ammonia nitrogen are used as the inputs of a support vector machine, and the optimal wavelet neural network based on particle swarm optimization algorithm is used to predict the overall state index of the water quality. The experimental results showed that the model is superior to the traditional BP neural network model, wavelet neural network model and gradient enhancement decision tree model [21].…”

Section: Introductionmentioning

confidence: 96%

Gaussian Process Regression for Prediction of Sulfate Content in Lakes of China

Zhao

Guo

Han

et al. 2019

J. Eng. Technol. Sci.

View full text Add to dashboard Cite

In recent years, environmental pollution has become more and more serious, especially water pollution. In this study, the method of Gaussian process regression was used to build a prediction model for the sulphate content of lakes using several water quality variables as inputs. The sulphate content and other variable water quality data from 100 stations operated at lakes along the middle and lower reaches of the Yangtze River were used for developing the four models. The selected water quality data, consisting of water temperature, transparency, pH, dissolved oxygen conductivity, chlorophyll, total phosphorus, total nitrogen and ammonia nitrogen, were used as inputs for several different Gaussian process regression models. The experimental results showed that the Gaussian process regression model using an exponential kernel had the smallest prediction error. Its mean absolute error (MAE) of 5.0464 and root mean squared error (RMSE) of 7.269 were smaller than those of the other three Gaussian process regression models. By contrast, in the experiment, the model used in this study had a smaller error than linear regression, decision tree, support vector regression, Boosting trees, Bagging trees and other models, making it more suitable for prediction of the sulphate content in lakes. The method proposed in this paper can effectively predict the sulphate content in water, providing a new kind of auxiliary method for water detection.

show abstract

“…Bu yüzden ülkemizde ve küresel çapta çok sayıda çalışma yapılmıştır. Bu çalışmaların bazıları veri toplayarak, deneysel şekilde ve zaman gerektirirken (Gedik ve arkadaşları [1], Kalyoncu ve diğerleri [2], Taş [3], Gültekin ve diğerleri [4], İleri ve arkadaşları [5], Cebe ve Barlas [6] ) , bazıları teorik ve pratik (Yenilmez ve Aksoy [7], Tomas ve diğerleri [8], Zhang ve arkadaşları [9], Tekşen Ercan ve Anagün [10]) çalışmalardır. Deneysel çalışmalardan olan Gedik ve arkadaşları [1] Doğu Karadeniz Bölgesi'ndeki Rize ilinde bulunan Fırtına Deresi'nin su kalitesi özelliklerini belirleyip önceki çalışmalarla karşılaştırmışlardır.…”

Section: Introductionunclassified

“…Çalışılan bölge için parçalı değişkenli doğrusal regresyon modelinin daha uygun olduğu sonucuna varmışlardır. Zhang ve diğerleri [9] Pekin'de mevcut çalışmalardan daha kapsamlı bir su kalitesi tahmin yöntemi geliştirmeyi amaçlamışlardır. Çalışmaları sonucunda parçacık sürü optimizasyonu tabanlı dalgacık sinir ağı yaklaşımı modelini önermişlerdir, model etkililiğini eldeki verilerle doğrulamışlardır.…”

Section: Introductionunclassified

Su Sertliğinin ANFIS ile Tahmin Edilmesi: Köprüçay Örneği

Saplioğlu¹,

Kucukerdem²

2018

acperpro

View full text Add to dashboard Cite

G&uuml;n&uuml;m&uuml;zde şehirleşme ile sanayileşmenin hızla artması ve iklim değişikliklerine sebep olan k&uuml;resel ısınma birtakım &ccedil;evre sorunlarını da beraberinde getirmektedir. Su kalitesinin değişimi de &ouml;nemli &ccedil;evre sorunlarının başında gelmektedir. Su kalitesi suyun fiziksel, kimyasal ve biyolojik &ouml;zellikleri hakkında fikir vermekte ve suyun kullanım amacına g&ouml;re değerlendirilmektedir. Su kalitesini etkileyen &ouml;nemli parametrelerden birisi de su sertliğidir. Bu &ccedil;alışmada suyun elektriksel iletkenlik, anyon veya katyon değerleri ve toplam tuz konsantrasyonu &ouml;zellikleri ile farklı girdi kombinasyonları uygulanıp, su sertliğinin tahmini i&ccedil;in Adaptif Ağ Tabanlı Bulanık &Ccedil;ıkarım Sistemi (ANFIS) kullanılarak birtakım modeller geliştirilmiştir.

show abstract

Development of a method for comprehensive water quality forecasting and its application in Miyun reservoir of Beijing, China

Cited by 44 publications

References 7 publications

An Occupational Disease Assessment of the Mining Industry’s Occupational Health and Safety Management System Based on FMEA and an Improved AHP Model

An Occupational Disease Assessment of the Mining Industry’s Occupational Health and Safety Management System Based on FMEA and an Improved AHP Model

Gaussian Process Regression for Prediction of Sulfate Content in Lakes of China

Su Sertliğinin ANFIS ile Tahmin Edilmesi: Köprüçay Örneği

Contact Info

Product

Resources

About