Estimation Of Values Research Articles

Influence of Iodine Chemistry in I2 Scrubbing Modeling

With the scrubbing of molecular iodine (I2) from gas streams in water pools at an accident site (boiling water reactor wetwell, filtered containment venting systems, etc.), some discernible impact on the aqueous radiochemistry of the I2 decontamination factor (DF) is expected, sometimes with hardly any effect on aerosol scrubbing. In the frame of the NUGENIA Integration of Pool Scrubbing Research to Enhance Source-Term Calculations (IPRESCA) project, the Central Research Institute of Electric Power Industry (CRIEPI) in Japan performed a series of tests to study the I2 scrubbing behavior at high pH values, with changing pH in the course of the tests. We used these data for our simulation analyses, and we obtained sensible estimates of the experimental DF values in many calculated cases. The employed tool for our simulations was a modified version of the SPARC code inside MELCOR. This program was used for the IPRESCA benchmark parametric calculations, where the pH-dependent effect of the iodine chemistry equilibria at the bubble-water interface was predicted to be significant. The same was true for our simulations in the CRIEPI experiments. We have now modeled not just the interface equilibria, but also some slower (kinetic-driven) chemical interactions in water, which would transform, at these high pH values, most of the I2 into nonvolatile aqueous iodine species. The overall chemistry effect is quite pronounced, like in the experiments, though the description of the bubble thermal hydraulics was at least of the same importance for modeling. Many open questions remain, one of the trickiest of which being the employment of radiochemistry models (relevant to real accident conditions) for explanations of experiments driven by the normal (thermal) chemistry of iodine.

NUMERICAL-ANALYTICAL METHOD OF DECOMPOSITION-AUTOCOMPENSATION FOR SOLVING THE SIGNAL RECOGNITION PROBLEM BASED ON INACCURATE OBSERVATIONS

A numerical-analytical method is developed to solve the problem of optimal recognition of a set of possible signals observed as an additive mixture containing not only a fluctuation observation error (with an unknown statistical distribution) but also a singular interference (with parametric uncertainty). The method allows for both the detection of signals present in the mixture and the estimation of their parameters within a specified quality criterion and associated constraints. The proposed method, based on the idea of generalized invariant-unbiased estimation of linear functional values, enables decomposition of the computational procedure and autocompensation of singular interference without resorting to the traditional expansion of the state space. Linear spectral decompositions in specified functional bases are used for the parametric finite-dimensional representation of signals and interference, while knowledge of the correlation matrix of the observation error is sufficient for error description. Random and systematic errors are analyzed, and an illustrative example is provided.

Study on Fire Characteristics of Flame-Retardant Polycarbonate Under Low Pressure

This work presents experimental and numerical research on the pyrolysis and combustion characteristics of flame-retardant polycarbonate under low ambient pressure. A novel experimental low-pressure combustion platform was constructed to determine the heat release rate, a key combustion parameter of polycarbonate. The ignition process of polycarbonate under external radiation was analyzed, and an ignition time prediction model was developed. In addition, theoretical calculations of the main gas components and concentrations during the pyrolysis stage of polycarbonate and estimations of the calorific values of the combustible gas components produced during pyrolysis were carried out, providing a new explanation for the phenomenon of advancing ignition time in low-pressure environments.

Endocrine-disrupting compounds in urban rivers of the southern border of Mexico: Occurrence and ecological risk assessment

The occurrence of seven endocrine-disrupting compounds (EDCs) in four urban rivers on the southern border of Mexico was studied in this work. The selected EDCs were 17β-estradiol (E2), estriol (E3), 17α-ethinylestradiol (EE2), bisphenol A (BPA), bisphenol F (BPF), 4-nonylphenol (4NP) and 4-tert-octylphenol (4TOP). Water samples from the Coatan, Texcuyuapan, Cahoacan, and Coatancito rivers were collected at three different sites on each river and processed by solid phase extraction (SPE). The samples were analyzed by gas chromatography triple quadrupole tandem mass spectrometry (GC-MS/MS) and compounds of interest were identified by dynamic mass reaction monitoring mode (dMRM). Among the target EDCs, E2, BPA, and 4NP were detected in all water samples, with BPA being the most abundant ranging from 4.22 up to 127.96 ng/L. Correlation tests showed significant positive associations between estrogens and BPA, as well as the correlation between alkylphenols and BPA, suggesting common origin emission sources, which were identified as discharges of untreated municipal wastewater. Finally, the estimation of RQ and EEQ values indicated that the presence of E2, E3, EE2, and BPA in all sampled points represents a high risk for aquatic life in these sites, mainly for Texcuyuapan River, where the aquatic organisms may be susceptible to endocrine disruption by chronic exposure to detected compounds.

A comprehensive analysis of the tail-dependent structure of wind loads and its engineering applications

Wind load field characteristics on the roof surface of low-rise buildings based on field measurements have crucial engineering guidance value. In the background, tail-dependence structure from measured wind loads can assist in modeling the joint tail distribution of multivariate wind loads. In this study, the non-parameter estimation method, multi-copula function model and multivariate peak over threshold model are applied to estimate its precise value. The upper tail dependence coefficient's value is around 0.20 when the quantile for p(y) = 0.75. When p(y) = 0.95, the Gumbel copula overestimates the tail-dependence value slightly. Additionally, the lower tail-dependence values estimated by the Clayton copula are around 0.19 at 0.25 quantile. For extreme tail-dependence coefficients, little difference exists in the estimated results by the non-parameter estimation method and the peak over threshold model, in which its value varies from 0.80 to 0.90. Under roof pitch = 5°, its value exhibits some dispersion at different locations. An area weight function is applied to estimate the extreme tail-dependence value between critical regions. Then, the expectation function of tail dependence reaches the peak value in p(x) = 0.50, p(y) = 0.50 and it has different gradients for different variables and tail regions. Additionally, the lower tail dependence structure is significantly stronger than the upper tail dependence for wind loads with negative skewness. For application in wind engineering, potential applications in risk analysis for roof structures, extreme value estimation for local region block wind load, and wind load forecast for unmonitored locations are proposed.

Bandwidth selection methods for non parametric regression with spatially correlated data

. In non parametric regression estimation, a critical and unavoidable step is to choose the smoothing parameters (bandwidth) to control the smoothness of the curve estimate. In the presence of spatially correlated errors, the traditional data-driven bandwidth selection methods, such as cross-validation and generalized cross-validation, do not work well for providing efficient bandwidth values. Moreover, the existing methods are based on estimation of correlation structure. As errors are unobservable, estimation of correlation is a big challenge. This article studies bandwidth selection methods for local linear regression (LLR) in the presence of correlated errors. For this purpose, we derive the weighted mean average square errors (WMASE) and use it along with bias-correlated generalized cross-validation (GCV) as bandwidth selection criterion. We then get the estimates of bandwidth by two ways: by minimizing the weighted mean average square errors (WMASE) and by using the bias-correlated generalized cross-validation (GCV) criterion. Due to its good properties, the composite likelihood (CL) is used to estimate the correlation. The results show that composite likelihood provides better estimates than maximum likelihood (ML) in the sense of producing more reasonable estimates of correlation parameters and bandwidth values. Also, our methods appear reasonably robust to the misspecification of the parametric correlation model. Moreover, the proposed methods work much better than ignoring the correlation and applying traditional methods. Finally, we apply our methods on water chemistry data collected about lakes in the Northeastern United States.

Inference of record failure times from unit generalized Rayleigh distribution

ABSTRACT In this paper, problems of estimation and prediction for record values are discussed for a two-parameter unit generalized Rayleigh distribution. Maximum likelihood estimators of model parameters along with their existence and uniqueness are established, and corresponding approximate confidence intervals are constructed based on asymptotic theory. In addition, alternative generalized inferential approach is provided for comparison based on the proposed pivotal quantities. Further, prediction intervals of remaining useful life are also presented under classical and generalized inferential methods when the unit generalized Rayleigh record values are available. Extensive numerical studies and two real-life examples are conducted to show the performance of the proposed methods. The results indicate that both classical and generalized estimation methods work satisfactorily and the proposed generalized inferential approach performs superior to traditional estimates in general.

Reduction of surface roughness in selectively etched microchannels in lithium niobate

By post-etching annealing, the roughness of microchannels fabricated by fs laser assisted selective etching could be reduced to values of 2 nm. The influence of inscription parameters and annealing conditions on the microchannels’ roughness and the evolution of their shape with annealing temperature and time have been investigated. A functional dependence enabling the estimation of roughness values resulting from certain processing parameters was determined. The low surface roughness achieved enables the transport of fluids with very low friction factors and optical-grade surfaces for the combination of microfluidic channels with optical waveguides, allowing the acousto-optical, electro-optical, and (nonlinear) optical properties of lithium niobate to be utilized for future monolithic optofluidic devices.

Regional calibration of the Hargreaves model for estimation of reference evapotranspiration

Abstract Estimation of reference evapotranspiration values is crucial in climatological and hydrological research, agricultural engineering, and irrigation design. The Penman-Monteith method, endorsed by the Food and Agriculture Organization (FAO) of the United Nations and numerous research studies, is widely regarded as the gold standard. However, its extensive data requirements limit its applicability in regions with sparse meteorological networks or limited measurement capabilities. The Hargreaves method, which requires only basic air temperature inputs, offers an alternative solution. The aims of this study were to calibrate the Hargreaves model for Central European climate conditions, considering altitudinal dependence, and to evaluate the temporal stability of the model parameters. In the first part of the research, we regionalized the Hargreaves coefficients using a curve-fitting method to ensure the best accuracy across 60 climatological stations in Slovakia. The regionalization of the Hargreaves coefficient improved accuracy by 10.1%, reducing the weighted absolute percentage error (WAPE) to 17.9%. However, our results showed that the accuracy of the modified Hargreaves model decreased with the increasing altitude of a climatological station. Incorporating altitude into the Hargreaves equation significantly improved model accuracy in stations at higher altitudes, providing a consistent level of accuracy across all climatological stations, regardless of their location and altitude. The results also indicated that the optimal model coefficient values change over time, showing a decreasing trend of –0.5 for the B coefficient and –0.1 for the C coefficient between the periods 1981–2000 and 2001–2020. Although regionalizing the Hargreaves model coefficients for local conditions can achieve good model performance, the model’s accuracy is not stable over time. Thus, periodic validation of the model is necessary for short-term applications.

Automated estimation of cementitious sorptivity via computer vision

Monitoring water uptake in cementitious systems is crucial to assess their durability against corrosion, salt attack, and freeze-thaw damage. However, gauging absorption currently relies on labor-intensive and infrequent weight measurements, as outlined in ASTM C1585. To address this issue, we introduce a custom computer vision model trained on 6234 images, consisting of 4000 real and 2234 synthetic, that automatically detects the water level in prismatic samples absorbing water. This model provides accurate and frequent estimations of water penetration values every minute. After training the model on 1440 unique data points, including 15 paste mixtures with varying water-to-cement ratios from 0.4 to 0.8 and curing periods of 1 to 7 days, we can now predict initial and secondary sorptivities in real time with high confidence, achieving R² > 0.9. Finally, we demonstrate its application on mortar and concrete systems, opening a pathway toward low-cost and automated durability assessment of construction materials.

Human Values Estimation on Articles by Extracting and Concatenating of Opinion Expressions

Human Values Estimation on Articles by Extracting and Concatenating of Opinion Expressions

Esophageal pressure as estimation of pleural pressure: a study in a model of eviscerated chest

BackgroundTranspulmonary pressure is the effective pressure across the lung parenchyma and has been proposed as a guide for mechanical ventilation. The pleural pressure is challenging to directly measure in clinical setting and esophageal manometry using esophageal balloon catheters was suggested for estimation. However, the accuracy of using esophageal pressure to estimate pleural pressure is debated due to variability in the mechanical properties of respiratory system, esophagus and esophageal catheter. Furthermore, while a vertical pleural pressure gradient exists across lung regions, esophageal pressure balloon provides a single value, representing, at most, the pressure surrounding the esophagus.MethodsIn a swine model with a preserved esophagus and a single homogenous, easily measurable intrathoracic pressure, we evaluated esophageal pressure’s agreement with intrathoracic pressure at different positive end-expiratory pressure (PEEP) levels (0, 5, 10, 15 cmH2O). We assessed the improvement of measurement accuracy by correcting absolute esophageal values using a previously described technique, that accounts for the pressure generated by the esophageal wall in response to esophageal balloon inflation.The study involved five swine, wherein two different esophageal catheters were used alongside the four distinct PEEP levels. Swings, uncorrected and corrected absolute esophageal pressures (end-inspiratory, end-expiratory) were compared with their respective intrathoracic pressures. The effect of correction technique was assessed with manual incremental step inflation procedure.ResultsWe found that both catheters significantly overestimated absolute esophageal pressure compared to intrathoracic pressure (5.01 ± 3.32 and 6.06 ± 5.62 cmH2O at end-expiration and end-inspiration, respectively), with error increasing at higher positive end-expiratory pressure levels (end-expiration: 2.36 ± 2.03, 3.77 ± 1.37, 6.24 ± 2.51 and 7.69 ± 4.02 for each PEEP level, P < 0.0001; end-inspiration: 1.71 ± 2.10, 3.70 ± 1.73, 7.67 ± 3.62 and 11.14 ± 7.60 for each PEEP level, P = 0.0004).Applying the correction technique significantly improved agreement for absolute values (0.82 ± 1.62 and 1.86 ± 3.94 cmH2O at end-expiration and end-inspiration, respectively). Esophageal pressure swings accurately estimated intrathoracic pressure swings at low-medium intrathoracic pressures (-0.64 ± 0.62, -0.07 ± 0.53, 1.43 ± 1.51, and 3.45 ± 3.94 at PEEP 0, 5, 10 and 15 cmH2O, respectively; P = 0.0197).ConclusionsThe correction technique, based on the mechanical response of esophageal wall to the balloon inflation, is fundamental for obtaining reliable estimations of absolute intrathoracic pressure values, and for ensuring its correct application in clinical setting.

ANALYSIS OF THE POSSIBILITIES OF MANUFACTURING FUNCTIONAL ELEMENTS USING THE FFF METHOD

The article presents the course and results of research aimed at assessing the strength and practical usability of a furniture hinge additively manufactured from thermoplastic material. The research activities included: development of design assumptions, adoption of target geometry, creation of a 3D-CAD model, preliminary strength analysis in the FEM environment, prototype manufacturing using FFF method with thermoplastic material (pet-g), and conducting tests under conditions similar to real ones. The hinge geometry was based on typical market-available design solutions, while considering the specifics of the adopted manufacturing method. Strength analysis via FEM was conducted on the 3D-CAD model, allowing estimation of stress values and determination of the suitability of the developed geometry for testing on a real model. Subsequently, research models were produced using FFF technology with various infill patterns: linear 30%, hexagonal 30%, linear 60%, hexagonal 60%, and solid 100%. Bench tests were conducted to determine the maximum load-bearing capacity of the hinge under perpendicular loading to the axis and to assess hinge wear under conditions simulating real-life door usage. The results revealed that the hinge with solid infill safely carried a load of 160 kg without damage, while the hinge with hexagonal 30% infill exhibited the lowest load-bearing capacity, failing at 85 kg. To determine the hinge's durability, the clearance at two reference points on the doors was measured.

Determination of geochemical stability of swamp ecosystems of the taiga zone of Western Siberia to anthropogenic impact

Relevance. The need for scientifically based regulation of impacts on wetland ecosystems taking into account their specificity and geochemical stability. Aim. To determine the geochemical stability of wetlands in the taiga zone of Western Siberia to pollutants for two typical cases associated with: 1) operation of sludge pits; 2) discharge of domestic and industrial wastewater. Methods. Mathematical modeling, statistical methods. Results and conclusions. The authors have carried out the analysis of the results of studies of the chemical composition of wetland waters and extracts from peat and mineral soils of wetlands in the taiga zone of Western Siberia (mainly in the Tomsk region, as well as in the adjacent territories of the Khanty-Mansiysk Autonomous Okrug, Novosibirsk and Omsk regions). They obtained the estimates of the average values of geochemical indicators of wetland waters and peat by the depth of the peat deposit in peat bogs with varying degrees of anthropogenic impact. The paper introduces the method for assessing the anthropogenic impact of wastewater discharge and geomigration on swamps in areas where oil and gas facilities are located (permissible concentrations in wastewater entering swamp ecosystems), taking into account the «geochemical background» and sorption capacity of peat. In particular, the authors substantiated and tested the method for assessing the values of permissible concentrations, which should be considered as a «relatively safe» level of impact on swamp ecosystems, at which secondary pollution of swamp waters is not expected. It is shown that anthropogenic changes are mainly limited vertically by the upper layer of the peat deposit up to 1–2 m, and horizontally (within the active horizon of the peat deposit) – by areas up to 100–200 m.

Comparison of Three Different IBD Vaccination Protocols in Broiler Chicken-Efficacy, Serological Baselines and Histo-Pathological Lesions in the Bursa of Fabricius.

Infectious bursal disease (IBD) is a highly infectious disease of chicken found in all latitudes, due to the very high resistance to environmental conditions and commonly used disinfectants of the IBD virus (IBDV). This study was conducted to evaluate three IBD vaccination protocols in broiler chicken in terms of their effectiveness (clinical observations and production performance of the flock), estimation of serological baseline values (with the use of two different commercial ELISA kits) and the degree of progression of BF lesions (histopathological lesion score (HLS)) after vaccination. The three protocols were (I) single vaccination using an intermediate plus vaccine, (II) double vaccination with an intermediate vaccine and (III) double vaccination with an intermediate plus vaccine. Birds on farms vaccinated with protocol II were characterized by the lowest antibody titers in both ELISA tests and the lowest average HLS. The highest IDEXX titers were obtained in birds vaccinated with protocol III, while in the BIOCHEK test the highest titers were obtained for birds vaccinated with protocol I. Protocols I and III were characterized by similar HLSs. Birds vaccinated with protocols I and III had higher immune uniformity. The estimated serological baseline values and the degree of HLSs presents a clear picture of the differences between the different vaccination protocols and allows their adaptation for different farms depending on the current IBD epidemiological situation.

An early economic evaluation of WireSafe™ to prevent guidewire retention in central venous catheter procedures

Background Guidewire retention (GWR) poses a patient safety risk during Central Venous Catheter (CVC) insertions and is listed as a ‘Never Event’ by the National Health Service England (NHSE). WireSafe™ is an intervention to prevent GWR, but its cost-effectiveness is uncertain. This study is an early economic evaluation comparing WireSafe™ to standard care from a UK healthcare perspective. Methods We conducted (i) a primary analysis of GWR related NHSE Never Events data in England between 2016 and 2020; and (ii) a cost-utility analysis, including healthcare costs and quality-adjusted life years (QALYS) for populations receiving CVC-insertions. We applied a cost-effectiveness threshold of £30,000 per QALY and considered three WireSafe™ costing scenarios (£18.50, £4.50, and £2.50). Results NHSE Never Events data showed 61 GWR cases, averaging 1 per month. Most incidents (92%) were identified during hospital stays, with one serious adverse outcome reported (peri-arrest). In a population of 200,000, we estimate WireSafe™ would prevent 59.92 wire retentions, 5.61 procedural adverse events, 0.3 cardiac adverse events, and 0.19 deaths, improving QALYs by 4.87. In the base case analysis WireSafe™ was not cost-effective and had an economically justifiable price of £2.44. There were high levels of uncertainty in the lowest cost-scenario (ICER 95% credible interval: Dominant; £793,398). Conclusions The health benefits of WireSafe™ are limited due to low GWR rates and high identification rates, making WireSafe™ viable only at low costs. Future research should prioritise obtaining more precise estimates of these parameter values which are key determinants of cost-effectiveness.

Natural frequency tree- versus conditional probability formula-based training for medical students’ estimation of screening test predictive values: a randomized controlled trial

BackgroundMedical students and professionals often struggle to understand medical test results, which can lead to poor medical decisions. Natural frequency tree-based training (NF-TT) has been suggested to help people correctly estimate the predictive value of medical tests. We aimed to compare the effectiveness of NF-TT with conventional conditional probability formula-based training (CP-FT) and investigate student variables that may influence NF-TT’s effectiveness.MethodsWe conducted a parallel group randomized controlled trial of NF-TT vs. CP-FT in two medical schools in South Korea (a 1:1 allocation ratio). Participants were randomly assigned to watch either NF-TT or CP-FT video at individual computer stations. NF-TT video showed how to translate relevant probabilistic information into natural frequencies using a tree structure to estimate the predictive values of screening tests. CP-FT video showed how to plug the same information into a mathematical formula to calculate predictive values. Both videos were 15 min long. The primary outcome was the accuracy in estimating the predictive value of screening tests assessed using multiple-choice questions at baseline, post-intervention (i.e., immediately after training), and one-month follow-up. The secondary outcome was the accuracy of conditional probabilistic reasoning in non-medical contexts, also assessed using multiple-choice questions, but only at follow-up as a measure of transfer of learning. 231 medical students completed their participation.ResultsOverall, NF-TT was not more effective than CP-FT in improving the predictive value estimation accuracy at post-intervention (NF-TT: 87.13%, CP-FT: 86.03%, p = .86) and follow-up (NF-TT: 72.39%, CP-FT: 68.10%, p = .40) and facilitating transfer of training (NF-TT: 75.54%, CP-FT: 71.43%, p = .41). However, for participants without relevant prior training, NF-TT was more effective than CP-FT in improving estimation accuracy at follow-up (NF-TT: 74.86%, CP-FT: 58.71%, p = .02) and facilitating transfer of learning (NF-TT: 82.86%, CP-FT: 66.13%, p = .04).ConclusionsIntroducing NF-TT early in the medical school curriculum, before students are exposed to a pervasive conditional probability formula-based approach, would offer the greatest benefit.Trial registrationKorea Disease Control and Prevention Agency Clinical Research Information Service KCT0004246 (the date of first trial registration: 27/08/2019). The full trial protocol can be accessed at https://cris.nih.go.kr/cris/search/detailSearch.do?seq=15616&search_page=L.

Comparing genomic studies in animal breeding and human genetics: Focus on disease-related traits in livestock.

Genomic studies of diseases can be divided into two types: (1) analyses that reveal causal genes by focusing on linkage disequilibrium between observed and causal variants and (2) those that simultaneously assess numerous genetic markers to estimate the polygenic effects of a particular genomic region or entire genome. The field of human genetics has emphasized the discovery of causal genes, but these represent only a fraction of the total genetic variance. Therefore, alternative approaches, such as the polygenic risk score, which estimates the genetic risk for a given trait or disease on the basis of all genetic markers (rather than on known causal variants only), have begun to garner attention. In many respects, these human genetic methods are similar to those originally developed for the estimation of breeding values (i.e., total additive genetic effects) in livestock. However, despite these similarities in methods, the fields of human and animal genetics still differ markedly in terms of research objectives, target populations, and other characteristics. For example, livestock populations have continually been selected and inbred throughout their history; consequently, their effective population size has shrunk and preferred genes (such as those influencing disease resistance and production traits) have accumulated in the modern breeding populations. By examining the characteristics of these two fields, particularly from the perspectives of disease and disease resistance, this review aims to improve understanding of the intrinsic differences between genomic studies using human compared with livestock populations.

Genotype-by-Trait (GT) biplot analysis and ranking of rice genotypes in salinity stress conditions

Estimation of plant tolerance values for agronomic traits, in addition to being genetically influenced, can also be influenced by the plant’s growing environment. Effective screening at the generative stage can only be carried out on land directly affected by salinity. However, the challenge lies in the fact that salinity levels vary widely on farmers’ land and are difficult to predict. The GT biplot analysis is a statistical method used in plant breeding to evaluate the performance of different genotypes based on various supporting traits. e three groups of biplots used are genotype by trait evaluation, genotype ranking analysis, and mega-environment analysis. There were differences in genotype responses based on yield component variables in each experimental environment. IRRI-IL12 and IRRI-IL09 are stable salinity-tolerant rice genotypes. IRRI-IL07 and IRRI-IL16 are adaptive in the optimum environment (L1), IRRI-IL07 and IRRI-IL10 are adaptive in the greenhouse salinity environment (L2), and IRRI-IL13 is adaptive in the salinated intrusion (L3).

UAV multispectral remote sensing for the estimation of SPAD values at various growth stages of maize under different irrigation levels

Chlorophyll is crucial for photosynthesis in plants and the readings by a SPAD meter (Soil and Plant Analyzer Development) can be used to represent leaf chlorophyll content for monitoring crop growth status and predicting grain yield. Remote sensing technology has shown potential in non-destructive monitoring of SPAD values over large areas, but current SPAD inversion models are limited in their ability to incorporate multiple principal components besides spectral parameters, adapt to other variables such as water stress, and predict SPAD only throughout the entire growth period. This two-year study used crop parameters (plant height and leaf area index) and vegetation indices (VI) derived from unmanned aerial vehicle (UAV) multispectral images to develop SPAD prediction models for maize under different irrigation levels in the 2018 and 2019 growing seasons in Inner Mongolia, China. Two nonlinear machine learning models, random forest (RF) and support vector regression (SVR), and a multiple statistical regression method (partial least squares regression (PLSR)) were used to modeling SPAD. The results showed that the VIs with a high correlation with SPAD varied at each growth stage and the accuracy of SPAD estimation model can be improved significantly by dividing different growth stages (R2 increased by more than 104 %). PLSR performed better than RF and SVR for each growth period, especially at the reproductive R stage (R2 = 0.79, RMSE = 2.25). LAI and PH did not always improve prediction accuracy, but adding crop parameters did increase the correlation coefficient between predicted values and biomass by 8.3 %. This study provides valuable insights into the estimation of SPAD at different growth stages of maize under varying water stress levels using UAV data and crop parameters, offering guidance for farmland management and yield prediction.