C. Díaz Muñiz
About
C. Díaz Muñiz is a scholar working on Industrial and Manufacturing Engineering, Water Science and Technology and Environmental Engineering.
According to data from OpenAlex, C. Díaz Muñiz has authored 29 papers receiving a total of 635 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Industrial and Manufacturing Engineering, 20 papers in Water Science and Technology and 19 papers in Environmental Engineering. Recurrent topics in C. Díaz Muñiz's work include Water Quality Monitoring and Analysis (24 papers), Hydrological Forecasting Using AI (19 papers) and Water Quality and Pollution Assessment (12 papers). C. Díaz Muñiz is often cited by papers focused on Water Quality Monitoring and Analysis (24 papers), Hydrological Forecasting Using AI (19 papers) and Water Quality and Pollution Assessment (12 papers). C. Díaz Muñiz collaborates with scholars based in Spain, Portugal and Australia. C. Díaz Muñiz's co-authors include J.R. Alonso Fernández, P.J. Garcı́a Nieto, Esperanza García–Gonzalo, Fernando Sánchez Lasheras, Francisco Javier de Cos Juez, J. Taboada, Javier Martínez Martínez, Juan Carlos Álvarez Antón, Carla Iglesias Comesaña and Víctor M. González and has published in prestigious journals such as The Science of The Total Environment, Journal of Hydrology and Environmental Science and Pollution Research.
In The Last Decade
C. Díaz Muñiz
29 papers receiving 621 citations
Peers
C. Díaz Muñiz
J.R. Alonso Fernández Spain
John Machell United Kingdom
Spencer Snowling Canada
Nguyen Thanh Giao Vietnam
Yifan Zhang China
Xiangyang Qi China
Kunlun Xin China
Chenguang Song China
Ling Yang China
Lihua Song China
Citations per year, relative to C. Díaz Muñiz C. Díaz Muñiz (= 1×)
peers
J.R. Alonso Fernández
Countries citing papers authored by C. Díaz Muñiz
Since
Specialization
Citations
This map shows the geographic impact of C. Díaz Muñiz's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by C. Díaz Muñiz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. Díaz Muñiz more than expected).
Fields of papers citing papers by C. Díaz Muñiz
Since
Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences
This network shows the impact of papers produced by C. Díaz Muñiz. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by C. Díaz Muñiz. The network helps show where C. Díaz Muñiz may publish in the future.
Co-authorship network of co-authors of C. Díaz Muñiz
This figure shows the co-authorship network connecting the top 25 collaborators of C. Díaz Muñiz. A scholar is included among the top collaborators of C. Díaz Muñiz based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with C. Díaz Muñiz. C. Díaz Muñiz is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
1.
García–Gonzalo, Esperanza, et al.. (2024). Forecast of chlorophyll-a concentration as an indicator of phytoplankton biomass in El Val reservoir by utilizing various machine learning techniques: A case study in Ebro river basin, Spain. Journal of Hydrology. 639. 131639–131639.
2.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2021). Modeling eutrophication risks in Tanes reservoir by using a hybrid WOA optimized SVR-relied technique along with feature selection based on the MARS approximation. Stochastic Environmental Research and Risk Assessment. 36(9). 2561–2580.
3.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2021). Modeling algal atypical proliferation in La Barca reservoir using L-SHADE optimized gradient boosted regression trees: a case study. Neural Computing and Applications. 33(13). 7821–7838.
4.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2020). A New Predictive Model for Evaluating Chlorophyll-a Concentration in Tanes Reservoir by Using a Gaussian Process Regression. Water Resources Management. 34(15). 4921–4941.
5.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, Fernando Sánchez Lasheras, J.R. Alonso Fernández, & C. Díaz Muñiz. (2019). A hybrid DE optimized wavelet kernel SVR-based technique for algal atypical proliferation forecast in La Barca reservoir: A case study. Journal of Computational and Applied Mathematics. 366. 112417–112417.
6.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, Fernando Sánchez Lasheras, et al.. (2018). Cyanotoxin level prediction in a reservoir using gradient boosted regression trees: a case study. Environmental Science and Pollution Research. 25(23). 22658–22671.
7.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2017). Predictive modelling of eutrophication in the Pozón de la Dolores lake (Northern Spain) by using an evolutionary support vector machines approach. Journal of Mathematical Biology. 76(4). 817–840.
8.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2016). A hybrid wavelet kernel SVM-based method using artificial bee colony algorithm for predicting the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain). Journal of Computational and Applied Mathematics. 309. 587–602.
9.
Rüdel, Heinz, C. Díaz Muñiz, Hemda Garelick, et al.. (2015). Consideration of the bioavailability of metal/metalloid species in freshwaters: experiences regarding the implementation of biotic ligand model-based approaches in risk assessment frameworks. Environmental Science and Pollution Research. 22(10). 7405–7421.
10.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2015). A hybrid PSO optimized SVM-based model for predicting a successful growth cycle of the Spirulina platensis from raceway experiments data. Journal of Computational and Applied Mathematics. 291. 293–303.
11.
Nieto, P.J. Garcı́a, Esperanza García–Gonzalo, J.R. Alonso Fernández, & C. Díaz Muñiz. (2015). Hybrid PSO–MARS–based model for forecasting a successful growth cycle of the Spirulina platensis from experimental data in open raceway ponds. Ecological Engineering. 81. 534–542.
12.
Nieto, P.J. Garcı́a, et al.. (2015). A hybrid PSO optimized SVM-based method for predicting of the cyanotoxin content from experimental cyanobacteria concentrations in the Trasona reservoir: A case study in Northern Spain. Applied Mathematics and Computation. 260. 170–187.
13.
Martínez, Javier Martínez, et al.. (2014). Analysis and detection of functional outliers in water quality parameters from different automated monitoring stations in the Nalón River Basin (Northern Spain). Environmental Science and Pollution Research. 22(1). 387–396.
14.
Muñiz, C. Díaz, J.R. Alonso Fernández, P.J. Garcı́a Nieto, & Juan Carlos Álvarez Antón. (2014). Modelling algal abnormal proliferation in a reservoir using support vector regression: a case study. Ecohydrology. 8(6). 1109–1118.
15.
Nieto, P.J. Garcı́a, J.R. Alonso Fernández, Francisco Javier de Cos Juez, Fernando Sánchez Lasheras, & C. Díaz Muñiz. (2013). Hybrid modelling based on support vector regression with genetic algorithms in forecasting the cyanotoxins presence in the Trasona reservoir (Northern Spain). Environmental Research. 122. 1–10.
16.
Vilán, J.A., J.R. Alonso Fernández, P.J. Garcı́a Nieto, et al.. (2013). Support Vector Machines and Multilayer Perceptron Networks Used to Evaluate the Cyanotoxins Presence from Experimental Cyanobacteria Concentrations in the Trasona Reservoir (Northern Spain). Water Resources Management. 27(9). 3457–3476.
17.
Martínez, Javier Martínez, et al.. (2013). Analysis and detection of outliers in water quality parameters from different automated monitoring stations in the Miño river basin (NW Spain). Ecological Engineering. 60. 60–66.
18.
Nieto, P.J. Garcı́a, J.R. Alonso Fernández, Fernando Sánchez Lasheras, Francisco Javier de Cos Juez, & C. Díaz Muñiz. (2012). A new improved study of cyanotoxins presence from experimental cyanobacteria concentrations in the Trasona reservoir (Northern Spain) using the MARS technique. The Science of The Total Environment. 430. 88–92.
19.
Fernández, J.R. Alonso, C. Díaz Muñiz, P.J. Garcı́a Nieto, et al.. (2012). Forecasting the cyanotoxins presence in fresh waters: A new model based on genetic algorithms combined with the MARS technique. Ecological Engineering. 53. 68–78.
20.
Muñiz, C. Díaz, P.J. Garcı́a Nieto, J.R. Alonso Fernández, Javier Martínez Martínez, & J. Taboada. (2012). Detection of outliers in water quality monitoring samples using functional data analysis in San Esteban estuary (Northern Spain). The Science of The Total Environment. 439. 54–61.
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