A new predictive model for the outlet turbidity in micro-irrigation sand filters fed with effluents using Gaussian process regression

Nieto, P.J. Garcı́a; García–Gonzalo, Esperanza; Puig‐Bargués, Jaume; Solé-Torres, Carles; Duran–Ros, Miquel; Arbat, Gerard

doi:10.1016/j.compag.2020.105292

Cited by 10 publications

(3 citation statements)

References 34 publications

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“…Ambiental, v.28, n.5, e274127, 2024. al., 2018) and, mainly, by a filtration system more efficient in removing suspended particles (García Nieto et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents

Paiva,

Batista,

Silva

et al. 2024

Rev. bras. eng. agríc. ambient.

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The canonical correlation is used to correlate groups of distinct variables. The objective of this study was to use canonical correlation analysis to evaluate the interaction between water quality attributes clogging-causing and the hydraulic performance of non-pressure compensating drippers operating with dilutions of aquaculture effluent in well water. The experiment was in a completely randomized design in a split-split-plot scheme with three replicates, with five dilutions in the plots (Dilution 1: 100% aquaculture effluent; Dilution 2: 75% aquaculture effluent + 25% well water; Dilution 3: 50% aquaculture effluent + 50% well water; Dilution 4: 25% aquaculture effluent + 75% well water; and Dilution 5: 100% well water), three emitters in the sub-plots (ST (1.6 L h-1), SL (1.6 L h-1) and NJ (1.7 L h-1)), and three operating times in the sub-subplots (0, 80 and 160 hours, in which 0 hours operating time means the start of evaluations). The statistical analyses performed were correlation matrix and canonical analysis. The canonical correlation analysis indicated that when the concentrations of attributes increase, the hydraulic performance of the drippers decreases. The interaction of this group of attributes indicates that the clogging of drippers operating with the five dilutions of aquaculture effluent in well water occurs by the combined action of physical, chemical, and biological agents. The ST dripper was the least sensitive to the group of quality attributes of the dilutions, whereas the most sensitive was the SL dripper.

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“…Ambiental, v.28, n.5, e274127, 2024. al., 2018) and, mainly, by a filtration system more efficient in removing suspended particles (García Nieto et al, 2020).…”

Section: Resultsmentioning

confidence: 99%

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents

Paiva,

Batista,

Silva

et al. 2024

Rev. bras. eng. agríc. ambient.

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“…As in SVR, kernel matrices are applied in this method. Gaussian process regression has been extensively used in various applications related to agriculture [244][245][246][247][248].…”

Section: Bayesian Methodsmentioning

confidence: 99%

Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review

et al. 2023

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Rapid advancements in technology, particularly in soil tools and agricultural machinery, have led to the proliferation of mechanized agriculture. The interaction between such tools/machines and soil is a complex, dynamic process. The modeling of this interactive process is essential for reducing energy requirements, excessive soil pulverization, and soil compaction, thereby leading to sustainable crop production. Traditional methods that rely on simplistic physics-based models are not often the best approach. Computational intelligence-based approaches are an attractive alternative to traditional methods. These methods are highly versatile, can handle various forms of data, and are adaptive in nature. Recent years have witnessed a surge in adapting such methods in all domains of engineering, including agriculture. These applications leverage not only classical computational intelligence methods, but also emergent ones, such as deep learning. Although classical methods have routinely been applied to the soil–machine interaction studies, the field is yet to harness the more recent developments in computational intelligence. The purpose of this review article is twofold. Firstly, it provides an in-depth description of classical computational intelligence methods, including their underlying theoretical basis, along with a survey of their use in soil–machine interaction research. Hence, it serves as a concise and systematic reference for practicing engineers as well as researchers in this field. Next, this article provides an outline of various emergent methods in computational intelligence, with the aim of introducing state-of-the-art methods to the interested reader and motivating their application in soil–machine interaction research.

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“…Previous studies on the filtration performance of micro-irrigation media have focused on turbidity [21,22] and filtered water quality fractions, which have been used to measure the filtration performance of different media. However, it is known that turbidity is only a proxy parameter to indicate the particulate content in water, and it does not accurately reflect the concentration of sediment impurities in the filtered water [23].…”

Section: Introductionmentioning

confidence: 99%

Comparative Study and Evaluation of Sediment Deposition and Migration Characteristics of New Sustainable Filter Media in Micro-Irrigation Sand Filters

Song,

Cai,

Zhai

et al. 2024

Sustainability

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The quartz sand filter medium used in micro-irrigation media filters has the disadvantages of short filtration cycle, surface filtration, and mining pollution. Selecting resources as new filter media is essential to improve the performance of the media filter and boost sustainable development. In this study, the traditional quartz sand filter medium and two new filter media were selected, and their corresponding filtration performances were comparatively studied. The influence of the type, particle size, and height of the filter medium on filtration performance was evaluated. The sediment content and distribution based on the size of particles in quartz sand, crushed glass, and glass bead filter layers was measured and analyzed. The hydraulic performance of different filter columns was analyzed. The results showed that for a given particle size, quartz sand exhibits the best sediment retention ability. This promoted the aggregation of small sediment particles into larger ones, whereas the crushed glass and bead glass filter layers promoted the splitting of large sediment particles into smaller ones, which enabled the reduction of blockage during the micro-irrigation process. The filtration rate of the quartz sand filter column exhibited the least fluctuation relative to crushed glass and glass bead filter media, and the pressure in each column exhibited a linear incremental change. In summary, glass microbeads are not suitable as filter material, crushed glass is suitable for general micro-irrigation systems, and quartz sand is suitable for micro-irrigation systems with elaborate filtration requirements. The findings of this study can provide theoretical guidance for the selection of the micro-irrigation filter material.

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A new predictive model for the outlet turbidity in micro-irrigation sand filters fed with effluents using Gaussian process regression

Cited by 10 publications

References 34 publications

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents

Canonical correlation between clogging agents and performance of drippers operating with aquaculture effluents

Application of Computational Intelligence Methods in Agricultural Soil–Machine Interaction: A Review

Comparative Study and Evaluation of Sediment Deposition and Migration Characteristics of New Sustainable Filter Media in Micro-Irrigation Sand Filters

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