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  "author": "Garcia del Toro, E.M., Francisco Mateo, L., 
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  "author": "Garcia del Toro, E.M., Francisco Mateo, L., 
            
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Garcia-Salgado, S., Isabel Mas-Lopez, M. y Angeles Quijano, M.",
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Garcia-Salgado, S., Isabel Mas-Lopez, M. y Angeles Quijano, M.",
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  "notes": "The Mar Menor is a Mediterranean coastal saltwater lagoon 
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  "notes": "The Mar Menor is a Mediterranean coastal saltwater lagoon 
            
96
(Murcia, Spain) that represents a unique ecosystem of vital importance 
96
(Murcia, Spain) that represents a unique ecosystem of vital importance 
            
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for the area, from both an economic and ecological point of view. 
97
for the area, from both an economic and ecological point of view. 
            
98
During the last decades, the intense agricultural activity has caused 
98
During the last decades, the intense agricultural activity has caused 
            
99
episodes of eutrophication due to the contribution of inorganic 
99
episodes of eutrophication due to the contribution of inorganic 
            
100
nutrients, especially nitrates. For this reason, it is important to 
100
nutrients, especially nitrates. For this reason, it is important to 
            
101
control the quality of the water discharged into the Mar Menor lagoon, 
101
control the quality of the water discharged into the Mar Menor lagoon, 
            
102
which can be performed through the measurement of dissolved oxygen 
102
which can be performed through the measurement of dissolved oxygen 
            
103
(DO). Therefore, this article aimed to predict the DO in the water 
103
(DO). Therefore, this article aimed to predict the DO in the water 
            
104
discharged into this lagoon through the El Albujon watercourse, for 
104
discharged into this lagoon through the El Albujon watercourse, for 
            
105
which two theoretical models consisting of a multiple linear 
105
which two theoretical models consisting of a multiple linear 
            
106
regression (MLR) and a back-propagation neural network (RPROP) were 
106
regression (MLR) and a back-propagation neural network (RPROP) were 
            
107
developed. Data of temperature, pH, nitrates, chlorides, sulphates, 
107
developed. Data of temperature, pH, nitrates, chlorides, sulphates, 
            
108
electrical conductivity, phosphates and DO at the mouth of this 
108
electrical conductivity, phosphates and DO at the mouth of this 
            
109
watercourse, between January 2014 and January 2021, were used. A 
109
watercourse, between January 2014 and January 2021, were used. A 
            
110
preliminary statistical study was performed to discard the variables 
110
preliminary statistical study was performed to discard the variables 
            
111
with the lowest influence on DO. Finally, both theoretical models were 
111
with the lowest influence on DO. Finally, both theoretical models were 
            
112
compared by means of the coefficient of determination (R-2), the root 
112
compared by means of the coefficient of determination (R-2), the root 
            
113
mean square errors (RMSE) and the mean absolute error (MAE), 
113
mean square errors (RMSE) and the mean absolute error (MAE), 
            
114
concluding that the neural network made a more accurate prediction of 
114
concluding that the neural network made a more accurate prediction of 
            
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DO.",
115
DO.",
            
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  "notes_translated": {
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  "notes_translated": {
            
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    "es": "The Mar Menor is a Mediterranean coastal saltwater lagoon 
117
    "es": "The Mar Menor is a Mediterranean coastal saltwater lagoon 
            
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(Murcia, Spain) that represents a unique ecosystem of vital importance 
118
(Murcia, Spain) that represents a unique ecosystem of vital importance 
            
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for the area, from both an economic and ecological point of view. 
119
for the area, from both an economic and ecological point of view. 
            
120
During the last decades, the intense agricultural activity has caused 
120
During the last decades, the intense agricultural activity has caused 
            
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episodes of eutrophication due to the contribution of inorganic 
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episodes of eutrophication due to the contribution of inorganic 
            
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nutrients, especially nitrates. For this reason, it is important to 
122
nutrients, especially nitrates. For this reason, it is important to 
            
123
control the quality of the water discharged into the Mar Menor lagoon, 
123
control the quality of the water discharged into the Mar Menor lagoon, 
            
124
which can be performed through the measurement of dissolved oxygen 
124
which can be performed through the measurement of dissolved oxygen 
            
125
(DO). Therefore, this article aimed to predict the DO in the water 
125
(DO). Therefore, this article aimed to predict the DO in the water 
            
126
discharged into this lagoon through the El Albujon watercourse, for 
126
discharged into this lagoon through the El Albujon watercourse, for 
            
127
which two theoretical models consisting of a multiple linear 
127
which two theoretical models consisting of a multiple linear 
            
128
regression (MLR) and a back-propagation neural network (RPROP) were 
128
regression (MLR) and a back-propagation neural network (RPROP) were 
            
129
developed. Data of temperature, pH, nitrates, chlorides, sulphates, 
129
developed. Data of temperature, pH, nitrates, chlorides, sulphates, 
            
130
electrical conductivity, phosphates and DO at the mouth of this 
130
electrical conductivity, phosphates and DO at the mouth of this 
            
131
watercourse, between January 2014 and January 2021, were used. A 
131
watercourse, between January 2014 and January 2021, were used. A 
            
132
preliminary statistical study was performed to discard the variables 
132
preliminary statistical study was performed to discard the variables 
            
133
with the lowest influence on DO. Finally, both theoretical models were 
133
with the lowest influence on DO. Finally, both theoretical models were 
            
134
compared by means of the coefficient of determination (R-2), the root 
134
compared by means of the coefficient of determination (R-2), the root 
            
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mean square errors (RMSE) and the mean absolute error (MAE), 
135
mean square errors (RMSE) and the mean absolute error (MAE), 
            
136
concluding that the neural network made a more accurate prediction of 
136
concluding that the neural network made a more accurate prediction of 
            
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DO."
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DO."
            
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