Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308478841> ?p ?o ?g. }
- W4308478841 abstract "Accurate forecasting techniques for a stochastic pattern of water demand are essential for any city that faces high variability in climate factors and a shortage of water resources. This study was the first research to assess the impact of climatic factors on urban water demand in Iraq, which is one of the hottest countries in the world. We developed a novel forecasting methodology that includes data preprocessing and an artificial neural network (ANN) model, which we integrated with a recent nature-inspired metaheuristic algorithm [marine predators algorithm (MPA)]. The MPA-ANN algorithm was compared with four nature-inspired metaheuristic algorithms. Nine climatic factors were examined with different scenarios to simulate the monthly stochastic urban water demand over 11 years for Baghdad City, Iraq. The results revealed that (1) precipitation, solar radiation, and dew point temperature are the most relevant factors; (2) the ANN model becomes more accurate when it is used in combination with the MPA; and (3) this methodology can accurately forecast water demand considering the variability in climatic factors. These findings are of considerable significance to water utilities in planning, reviewing, and comparing the availability of freshwater resources and increasing water requests (i.e., adaptation variability of climatic factors)." @default.
- W4308478841 created "2022-11-12" @default.
- W4308478841 creator A5001560196 @default.
- W4308478841 creator A5024275698 @default.
- W4308478841 creator A5030041439 @default.
- W4308478841 creator A5032550331 @default.
- W4308478841 creator A5051240230 @default.
- W4308478841 creator A5070829177 @default.
- W4308478841 creator A5077858988 @default.
- W4308478841 creator A5081391850 @default.
- W4308478841 date "2023-01-01" @default.
- W4308478841 modified "2023-10-06" @default.
- W4308478841 title "Assessing the Benefits of Nature-Inspired Algorithms for the Parameterization of ANN in the Prediction of Water Demand" @default.
- W4308478841 cites W1974853958 @default.
- W4308478841 cites W2049786051 @default.
- W4308478841 cites W2062577207 @default.
- W4308478841 cites W2065902166 @default.
- W4308478841 cites W2069911320 @default.
- W4308478841 cites W2151554678 @default.
- W4308478841 cites W2163665747 @default.
- W4308478841 cites W2343616468 @default.
- W4308478841 cites W2483291099 @default.
- W4308478841 cites W2587001484 @default.
- W4308478841 cites W2588678793 @default.
- W4308478841 cites W2600845876 @default.
- W4308478841 cites W2622713141 @default.
- W4308478841 cites W2792319327 @default.
- W4308478841 cites W2795201804 @default.
- W4308478841 cites W2811140076 @default.
- W4308478841 cites W2836147354 @default.
- W4308478841 cites W2893630142 @default.
- W4308478841 cites W2896598631 @default.
- W4308478841 cites W2899462220 @default.
- W4308478841 cites W2903347319 @default.
- W4308478841 cites W2905155359 @default.
- W4308478841 cites W2943751924 @default.
- W4308478841 cites W2966284335 @default.
- W4308478841 cites W2970739080 @default.
- W4308478841 cites W2974234787 @default.
- W4308478841 cites W2976818350 @default.
- W4308478841 cites W2984191725 @default.
- W4308478841 cites W2985033708 @default.
- W4308478841 cites W3000563552 @default.
- W4308478841 cites W3003244122 @default.
- W4308478841 cites W3004018505 @default.
- W4308478841 cites W3007587653 @default.
- W4308478841 cites W3008681483 @default.
- W4308478841 cites W3011104345 @default.
- W4308478841 cites W3014974411 @default.
- W4308478841 cites W3019785922 @default.
- W4308478841 cites W3023846105 @default.
- W4308478841 cites W3024940778 @default.
- W4308478841 cites W3025548389 @default.
- W4308478841 cites W3027953868 @default.
- W4308478841 cites W3030526206 @default.
- W4308478841 cites W3033768870 @default.
- W4308478841 cites W3033842568 @default.
- W4308478841 cites W3039083873 @default.
- W4308478841 cites W3041888814 @default.
- W4308478841 cites W3043476082 @default.
- W4308478841 cites W3048448981 @default.
- W4308478841 cites W3056359467 @default.
- W4308478841 cites W3081063323 @default.
- W4308478841 cites W3095637457 @default.
- W4308478841 cites W3108440751 @default.
- W4308478841 cites W3109795660 @default.
- W4308478841 cites W3115412777 @default.
- W4308478841 cites W3123920941 @default.
- W4308478841 cites W3130047495 @default.
- W4308478841 cites W3151899409 @default.
- W4308478841 cites W3160309102 @default.
- W4308478841 cites W3200918440 @default.
- W4308478841 cites W4205813359 @default.
- W4308478841 cites W4210582231 @default.
- W4308478841 cites W4213308398 @default.
- W4308478841 cites W4225877522 @default.
- W4308478841 cites W4238746485 @default.
- W4308478841 doi "https://doi.org/10.1061/(asce)wr.1943-5452.0001602" @default.
- W4308478841 hasPublicationYear "2023" @default.
- W4308478841 type Work @default.
- W4308478841 citedByCount "3" @default.
- W4308478841 countsByYear W43084788412023 @default.
- W4308478841 crossrefType "journal-article" @default.
- W4308478841 hasAuthorship W4308478841A5001560196 @default.
- W4308478841 hasAuthorship W4308478841A5024275698 @default.
- W4308478841 hasAuthorship W4308478841A5030041439 @default.
- W4308478841 hasAuthorship W4308478841A5032550331 @default.
- W4308478841 hasAuthorship W4308478841A5051240230 @default.
- W4308478841 hasAuthorship W4308478841A5070829177 @default.
- W4308478841 hasAuthorship W4308478841A5077858988 @default.
- W4308478841 hasAuthorship W4308478841A5081391850 @default.
- W4308478841 hasBestOaLocation W43084788411 @default.
- W4308478841 hasConcept C11413529 @default.
- W4308478841 hasConcept C119857082 @default.
- W4308478841 hasConcept C132651083 @default.
- W4308478841 hasConcept C138885662 @default.
- W4308478841 hasConcept C153823671 @default.
- W4308478841 hasConcept C18903297 @default.
- W4308478841 hasConcept C194051981 @default.
- W4308478841 hasConcept C2778137410 @default.