Initial Estimates Research Articles

Characterization of Candidate Solutions for X-Ray Pulsar Navigation

X-ray pulsar based navigation (XNAV) can be used to estimate spacecraft state information based on observation of distant pulsars. XNAV system concepts typically require an initial position estimate since there are many candidate positions which may produce the same measurement. If position ambiguity can be resolved, XNAV may enable full state estimation without prior information. This study seeks to efficiently find candidate spacecraft positions and determine how to select pulsars to minimize the number of candidate solutions within a given domain. A numeric scheme for determining candidate positions is developed for an arbitrary number of observed pulsars. Pulsar selection criteria are developed in terms of relative direction, period, and phase accuracy. Results indicate that it is more time efficient to observe additional pulsars rather than improve the accuracy of pulsar measurements. A smaller angular separation and increased period of the observed pulsars reduces the number of candidate solutions within a given domain. Phase measurement accuracy should be improved simultaneously for all pulsars rather than prioritizing a single pulsar. These selection criteria are verified by evaluating the number of candidate solutions for permutations of 34 real pulsars.

Book Review of Global Drought and Flood: Monitoring,Prediction,and Adaptation

Global Drought and Flood: Monitoring, Prediction, and Adaptation is an American Geophysical Union monograph (published by Wiley) that introduces the latest advancements in physical and remote sensing models developed for drought and flood issues. The book consists of 18 chapters in 3 parts, which introduce global remote sensing monitoring of droughts and floods, modeling and prediction of global drought and flood, as well as risk assessment, management, and socioeconomic responses to global drought and flood. Current remote sensing observation research suggests that merging climate data can generate longer records suitable for drought assessment and monitoring, while some variables such as snow and relative humidity can be integrated into drought monitoring models to improve the monitoring and estimation of drought initiation, respectively. However, changes in satellite sensors also introduce considerable unquantifiable uncertainty to drought modeling. An ideal approach to this issue is to provide uncertainty boundaries based on top of the original observations. This uncertainty and the structural and parameter uncertainties generated by model-based simulations can be combined to assist decision-making in operational applications. The monograph not only elaborates on the dominant models, methods, techniques, and products used in practical applications internationally but also provides planning and deployment for flood disaster prediction. The drought and flood modeling and remote sensing methods presented in this book can be used for reference and use by global emergency organizations and decision-makers.

An analytical investigation into the lateral load response of curved RC shear walls

SummaryCurved structural elements can extensively be employed in engineering applications, to which structural designers and architects can resort in order to cope with the existing structural limitations and architectural challenges. In this regard, the current study is an attempt to provide insight into the overall performance of curved reinforced concrete (RC) shear walls (CRCSWs) due to the gaps existing in the literature. In order to fulfill this purpose, a CRCSW with general cross‐section has been considered subjected to the applied bi‐lateral and axial loadings. Equivalent non‐rectangular T‐, U‐, and L‐shaped sections are then introduced in lieu of a curved section. Thereafter, the stress and displacement distributions of CRCSWs have been analytically established. In order to highlight the structural merits of CRCSWs, a comparative study is performed based on the six non‐dimensional parameters defined in this study. According to the comparative study conducted between the CRCSWs and the equivalent non‐rectangular flanged walls, unlike latter wall types, the shear‐lag effects do not make serious issues for the performance of CRCSWs. Furthermore, to make a more realistic judgment on the response of CRCSWs, a numerical investigation has been carried out utilizing the finite element (FE) software Abaqus. On the strength of the data obtained from the FE simulation of 90 CRCSWs in three categories of short, squat, and slender walls, a regression model has been established, which is advantageous in that it can supply a means for the initial estimation of the shear strength of CRCSWs. The average R‐factor of 0.88 indicates that the established formulations can potentially well predict the shear strength of CRCSWs. The findings of this study divulge that, in addition to the inherent aesthetical advantages of CRCSWs, these structural elements can effectively resist against bi‐directional loadings as compared with the equivalent RC walls with flanged sections.

Validated assessment of power plant components with flaws and defects operating under long-term creep and isothermal creep-fatigue loading

An extensive database of frequently used heat-resistant steels 1 %Cr, 9–10 %Cr and 12 %Cr steels at application-typical temperatures was evaluated using the Nikbin-Smith-Webster model. Influencing factors, such as the initial plasticization and the specimen thickness, were investigated in the evaluation of the fracture mechanics material characteristic values. A thickness influencing factor fB for crack initiation is proposed, which improves the crack initiation estimation using the NSW model and reduces its over-conservatism notably. It could be shown that the crack initiation and especially the crack growth under creep loading can be described with sufficient accuracy by the modification of the NSW model. The limitation in the application of the C*-parameter could also be shown and explained by the Two-Criteria-Diagram (2CD). It should be applied to crack geometries with predominant crack tip damage. The 2CD is shown as preferred method for a more precise, material-related understanding and assessment of the crack initiation process.Based on the recalculation of fracture mechanics tests on CT und DENT specimens, the analytical approaches for the description of crack initiation and growth under creep and isothermal creep-fatigue loading could be validated in the long-term range by comparison with the experimental results up to 100,000 h.Finally, the transferability of these approaches from CT und DENT specimens to large components was investigated by calculating cracked components under practical creep and isothermal creep fatigue loading using these methods. It has been shown that the load level and the duration of holding time are decisive for the crack initiation and the crack growth under isothermal creep-fatigue loading. In the case of high stress and shorter holding times, the damage is predominantly influenced by fatigue. With lower stress and longer holding times, creep plays a more important role.

Initial Pole Axis and Spin Direction Estimation of Asteroids Using Infrared Imagery

Knowing the pole axis of an asteroid is vital to autonomous asteroid exploration efforts. Ground-based initial pole estimation methods are time and data intensive and produce estimates with large uncertainties. These errors have a significant impact on proximity navigation, shape modeling, and scientific data for small body missions. In this paper, a new method of obtaining this information from onboard spacecraft imagery is presented. The proposed method estimates the pole from onboard infrared imagery using the camera-asteroid geometry. This method does not require a prior and is designed to work in a vast majority approach trajectories due to the use of infrared images. The method is applied to simulated infrared images of asteroids 101955 Bennu and 25143 Itokawa as well as real infrared images of asteroid 162173 Ryugu from the Hayabusa2 mission. The average pole errors using this method on Bennu and Itokawa images are approximately 2 and 6 deg, respectively. The pole estimate error on the Ryugu images is approximately 8 deg. The algorithm is shown to be sensitive to the percentage of spin period imaged and the spacing between the images.

Improved softened truss model of prestressed concrete box girders subjected to combined bending and torsion

Prestressed concrete (PC) box girder is an innovative structure that is widely used in large-span bridges. Under eccentric loads such as vehicles, PC girders are inevitably under combined bending and torsion. To study its bending-torsional behavior, a refined full-range analysis model based on the combined action softening truss model (CA-STM) was proposed, where a simple and effective solution procedure and failure criteria were provided. The equilibrium equation, initial estimation equation for torque, and material constitutive model were modified by considering the prestressing effect to improve the CA-STM. An optimized algorithm was also employed to simplify the solution procedure instead of the traditional trial-and-error method, thus increasing the solution rate and stability. The theoretical curves predicted from the improved CA-STM exhibited great agreement with the available experimental results, and the predicted cracking and ultimate loads were also close to the experimental values. Hence, the improved CA-STM can reasonably predict the full-range mechanical response and failure modes of PC box girders subjected to combined bending and torsion, which provides great support to the design evaluation of such bridges.

Precision of diamond turning sinusoidal structures as measurement standards used to assess topography fidelity

In optical surface metrology, it is crucial to assess the fidelity of the topography measuring signals. One parameter to quantify this is the small-scale fidelity limit T FIL defined in ISO 25 178-600:2019. To determine this parameter, sinusoidal structures are generated, where the wavelengths are modulated according to a discrete chirp series. The objects are produced by means of ultra-precision diamond face turning. Planar areas and regions with slopes below 4° could be produced with form deviations of ≲10 nm. An initial estimate of the cutting tool’s nose radius resulted in a deviation that caused the ridges of the structures to be too narrow by approximately 150 nm, while the trenches were too wide. At the bottom of narrow trenches, deviations are observed in the form of elevations with heights of about 20 to 100 nm. The measurement standard investigated in this study has also been used to characterise optical instruments in a round-robin test within the European project TracOptic, which requires precise knowledge of the geometry of all structures. The geometry of the topography, cosine structures superimposed with form deviations, was measured using the Met. LR-AFM metrological long-range atomic force microscope of the German National Metrology Institute.

Herpes Zoster Recurrence: A Narrative Review of the Literature.

Herpes zoster (HZ; shingles) is a painful, cutaneous disease caused by reactivation of the varicella zoster virus, which causes varicella (chickenpox) typically during childhood. The considerable healthcare burden of HZ is relatively well documented, with approximately one in three individuals experiencing at least one episode during their lifetime, debilitating symptoms including neuropathic pain, and complications such as post-herpetic neuralgia, vision loss, and rarely, stroke, and increased severity in immunocompromised individuals. However, we are not aware of a comprehensive review of literature specifically examining the burden of HZ recurrence. We conducted a PubMed search (1 January 2003-2 February 2023) to assess available literature on the incidence, risk factors, and clinical features of HZ recurrence. The incidence of HZ recurrence reported by the studies identified was wide ranging. Studies in general populations of immunocompetent or immunocompetent/immunosuppressed (mixed) populations with an initial HZ episode estimate that approximately 1.2-9.6% of individuals may experience HZ recurrence, with an incidence rate of 1.7-16.6 cases per 1000 person-years. HZ recurrence was reported in 0.0-18.2% of immunocompromised individuals with HZ, with an incidence rate of 17.0-55 cases per 1000 person-years. Incidence rates varied according to study design, follow-up, and study populations. Recognized risk factors for HZ recurrence include immunocompromised status, female sex, family history, and comorbidities such as diabetes. Other factors that may predispose individuals to recurrence include long-lasting pain after the initial HZ episode and the presence of herpes zoster ophthalmicus. Our review underlines that following an initial HZ episode, individuals remain at risk of HZ recurrence, adding to the disease burden in a population. As HZ is preventable by vaccination, national HZ vaccination recommendations should include the need for and timing of vaccination in both immunocompetent and immunocompromised individuals who have a history of HZ.

Skeleton-based Human Activity Classification in Sparse Image Sequences

Research results on human activity classification in video are described, based on initial human skeleton estimation in video frames. Both single person actions and two-person interactions are considered. The initial skeleton data is estimated in selected video frames by OpenPose, HRNet or other dedicated library. Important contributions of presented work are computational steps of skeleton tracking and -refinement, and relational feature extraction from pairs of skeleton joints. It is shown, that this feature engineering significantly increases the classification accuracy. Regarding the final neural network encoder-classifier, two different architectures are designed and tested. The first solution is a lightweight MLP network, implementing the idea of a "mixture of pose experts". Several pose classifiers (experts) are trained independently on different time periods (snapshots) of single-person visual actions (or 2-person interactions), while the final classification is a time-related pooling of weighted expert classifications. All pose experts use the same deep encoding network. The second (middle weight) solution is based on a LSTM network.Both solutions are trained and tested on the action set of the well-known NTU RGB+D dataset, although only 2D data are used.Our results show comparable performance with some of the best reported STM- and CNN-based classifiers for this dataset. We conclude that by reducing the noise of skeleton data, highly successful lightweight- and midweight-approaches to visual activity recognition in image sequences can be achieved.

Enhanced Volts-per-Hertz Sensorless Starting of Permanent Magnet Motor with Heavy Loads in Long-Cable Subsea Applications

Permanent magnet (PM) motors are gaining prominence in subsea applications such as drilling, pumping, and boosting for oil and natural gas extraction. These motors are gradually replacing traditional induction motors. However, starting and operating PM motors at low speeds under heavy loads poses significant challenges. This is because of unknown initial rotor positions and resistive voltage drops due to the presence of a sinewave filter, transformer, and long cable. An unknown rotor position may result in temporary reverse speed, which may cause a loss of synchronism; therefore, initial rotor position estimation is preferable. Additionally, addressing the voltage drop issue requires careful voltage compensation to avoid transformer core saturation. In this paper, an enhanced V/Hz starting of a PM motor is proposed with initial position detection (IPD) and voltage compensation to start the motor reliably with a heavy load. The proposed control method is verified with controller hardware in the loop (C-HIL) real-time simulation using a Typhoon HIL-604 emulator and a Texas Instruments TMS320F28335 digital signal processor (DSP) control card.

A Light Multi-View Stereo Method with Patch-Uncertainty Awareness.

Multi-view stereo methods utilize image sequences from different views to generate a 3D point cloud model of the scene. However, existing approaches often overlook coarse-stage features, impacting the final reconstruction accuracy. Moreover, using a fixed range for all the pixels during inverse depth sampling can adversely affect depth estimation. To address these challenges, we present a novel learning-based multi-view stereo method incorporating attention mechanisms and an adaptive depth sampling strategy. Firstly, we propose a lightweight, coarse-feature-enhanced feature pyramid network in the feature extraction stage, augmented by a coarse-feature-enhanced module. This module integrates features with channel and spatial attention, enriching the contextual features that are crucial for the initial depth estimation. Secondly, we introduce a novel patch-uncertainty-based depth sampling strategy for depth refinement, dynamically configuring depth sampling ranges within the GRU-based optimization process. Furthermore, we incorporate an edge detection operator to extract edge features from the reference image's feature map. These edge features are additionally integrated into the iterative cost volume construction, enhancing the reconstruction accuracy. Lastly, our method is rigorously evaluated on the DTU and Tanks and Temples benchmark datasets, revealing its low GPU memory consumption and competitive reconstruction quality compared to other learning-based MVS methods.

Assessment of thermal and radiation induced creep in the dual cooled lead lithium blanket

The creep in recently designed blanket for the fusion nuclear science facility is described by decomposing it into thermal, irradiation and cavity swelling creep. Initial estimates of thermal creep using elastic high temperature rules showed that the recent heat transfer improvements at the first wall (FW) is feasible, and the FW can withstand heat flux of 0.35 MW/m2 at 3000 hrs without rupture. A viscoplastic model that is based on Norton's power law and relies on Multiphysics coupling of solid mechanics and heat transfer modules is used to capture the inelastic deformation in the blanket. Results showed that the design peak heat flux of 0.25 MW/m2 produced maximum thermal creep strain of 0.45 % and the relaxation of the thermal stress at the FW. Irradiation creep is prescribed to be proportional to the displacement damage dose and applied stress. The displacements from irradiation creep radially decrease from the FW to the back wall, but the maximum deformation is found at the back wall that is connected to the Helium manifold due to the high stresses at the region. Cavity swelling creep is dominant at steady state and combined with radiation creep to produce displacement of about 8 mm at the FW.

Integrating conceptual and machine learning models to enhance daily-Scale streamflow simulation and assessing climate change impact in the watersheds of the Godavari basin, India

This study examined and addressed climate change's effects on hydrological patterns, particularly in critical places like the Godavari River basin. This study used daily gridded rainfall and temperature datasets from the Indian Meteorological Department (IMD) for model training and testing, 70% and 30%, respectively. To anticipate future hydrological shifts, the study harnessed the EC-Earth3 data, presenting an innovative methodology tailored to the unique hydrological dynamics of the Godavari River basin. The Sacramento model provided initial streamflow estimates for Kanhargaon, Nowrangpur, and Wairagarh. This approach melded traditional hydrological modeling with advanced multi-layer perceptron (MLP) capabilities. When combined with parameters like lagged rainfall, lagged streamflow, potential evapotranspiration (PET), and temperature variations, these initial outputs were further refined using the Sac-MLP model. A comparison with Sacramento revealed the superior performance of the Sac-MLP model. For instance, during training, the Nash Sutcliffe efficiency (NSE) values for the Sac-MLP witnessed an improvement from 0.610 to 0.810 in Kanhargaon, 0.580 to 0.692 in Nowrangpur, and 0.675 to 0.849 in Wairagarh. The results of the testing further corroborated these findings, as evidenced by the increase in the NSE for Kanhargaon from 0.890 to 0.910. Additionally, Nowrangpur and Wairagarh experienced notable improvements, with their NSE values rising from 0.629 to 0.785 and 0.725 to 0.902, respectively. Projections based on EC-Earth3 data across various scenarios highlighted significant shifts in rainfall and temperature patterns, especially in the far future (2071–2100). Regarding the relative change in annual streamflow, Kanhargaon projections under SSP370 and SSP585 for the far future indicate increases of 584.38% and 662.74%. Similarly, Nowrangpur and Wairagarh are projected to see increases of 98.27% and 114.98%, and 81.68% and 108.08%, respectively. This study uses EC-Earth3 estimates to demonstrate the Sac-MLP model's accuracy and importance in climate change water resource planning. The unique method for region-specific hydrological analysis provides vital insights for sustainable water resource management. This research provides a deeper understanding of climate-induced hydrological changes and a robust modeling approach for accurate predictions in changing environmental conditions.

Developing questions to assess and measure patients’ perceived survival benefit from adjuvant endocrine therapy in breast cancer: a mixed methods pilot study

This mixed method study developed multiple question types to understand and measure women’s perceived benefit from adjuvant endocrine therapy. We hypothesis that patients do not understand this benefit and sought to develop the questions needed to test this hypothesis and obtain initial patient estimates. From 8/2022 to 3/2023, qualitative interviews focused on assessing and modifying 9 initial varied question types asking about the overall survival (OS) benefit from adjuvant endocrine therapy. Subsequent focus groups modified and selected the optimal questions. Patients’ self-assessment of their OS benefit was compared to their individualized PREDICT model results. Fifty-three patients completed the survey; 42% Hispanic, 30% rural, and 47% with income < $39,999 per year. Patients reported adequate health care literacy (61.5%) and average confidence about treatment and medication decisions 49.4 (95% CI 24.4–59.5). From the original 9 questions, 3 modified questions were ultimately found to capture patients’ perception of this OS benefit, focusing on graphical and prose styles. Patients estimated an OS benefit of 42% compared to 4.4% calculated from the PREDICT model (p < 0.001). In this group with considerable representation from ethnic minority, rural and low-income patients, qualitative data showed that more than one modality of question type was needed to clearly capture patients’ understanding of treatment benefit. Women with breast cancer significantly overestimated their 10-year OS benefit from adjuvant endocrine therapy compared to the PREDICT model.

Objective image quality assurance in cone-beam CT: Test methods, analysis, and workflow in longitudinal studies.

Standards for image quality evaluation in multi-detector CT (MDCT) and cone-beam CT (CBCT) are evolving to keep pace with technological advances. A clear need is emerging for methods that facilitate rigorous quality assurance (QA) with up-to-date metrology and streamlined workflow suitable to a range of MDCT and CBCT systems. To evaluate the feasibility and workflow associated with image quality (IQ) assessment in longitudinal studies for MDCT and CBCT with a single test phantom and semiautomated analysis of objective, quantitative IQ metrology. A test phantom (CorgiTM Phantom, The Phantom Lab, Greenwich, New York, USA) was used in monthly IQ testing over the course of 1 year for three MDCT scanners (one of which presented helical and volumetric scan modes) and four CBCT scanners. Semiautomated software analyzed image uniformity, linearity, contrast, noise, contrast-to-noise ratio (CNR), 3D noise-power spectrum (NPS), modulation transfer function (MTF) in axial and oblique directions, and cone-beam artifact magnitude. The workflow was evaluated using methods adapted from systems/industrial engineering, including value stream process modeling (VSPM), standard work layout (SWL), and standard work control charts (SWCT) to quantify and optimize test methodology in routine practice. The completeness and consistency of DICOM data from each system was also evaluated. Quantitative IQ metrology provided valuable insight in longitudinal quality assurance (QA), with metrics such as NPS and MTF providing insight on root cause for various forms of system failure-for example, detector calibration and geometric calibration. Monthly constancy testing showed variations in IQ test metrics owing to system performance as well as phantom setup and provided initial estimates of upper and lower control limits appropriate to QA action levels. Rigorous evaluation of QA workflow identified methods to reduce total cycle time to ∼10min for each system-viz., use of a single phantom configuration appropriate to all scanners and Head or Body scan protocols. Numerous gaps in the completeness and consistency of DICOM data were observed for CBCT systems. An IQ phantom and test methodology was found to be suitable to QA of MDCT and CBCT systems with streamlined workflow appropriate to busy clinical settings.

Method to derive the infrared complex refractive indices n(λ) and k(λ) for organic solids from KBr pellet absorption measurements.

Obtaining the complex refractive index vectors n(ν~) and k(ν~) allows calculation of the (infrared) reflectance spectrum that is obtained from a solid in any of its many morphological forms. We report an adaptation to the KBr pellet technique using two gravimetric dilutions to derive quantitative n(ν~)/k(ν~) for dozens of powders with greater repeatability. The optical constants of bisphenol A and sucrose are compared to those derived by other methods, particularly for powdered materials. The variability of the k values for bisphenol A was examined by 10 individual measurements, showing an average coefficient of variation for k peak heights of 5.6%. Though no established standards exist, the pellet-derived k peak values of bisphenol A differ by 11% and 31% from their single-angle- and ellipsometry-derived values, respectively. These values provide an initial estimate of the precision and accuracy of complex refractive indices that can be derived using this method. Limitations and advantages of the method are discussed, the salient advantage being a more rapid method to derive n/k for those species that do not readily form crystals or specular pellets.

Stabilization of Fuzzy Prey-Predator Model Using Backstepping Method

Ecological system depends on prey predator interaction and therefore, as a result, diseases may spread among prey or predator or both of them. In this work, the fuzzy logic-based systems are used to elaborate a prey-predator model to study the effect of varying in the inflection rate. Formulation of prey predator model using fuzzy logic is more realistic depiction of the phenomena, since the initial population estimates may not be precisely known in the real-life situation, therefore the initial conditions may also be considered as fuzzy. The dynamical behaviour of the fuzzy exploited system is studied by using the backstepping method. Some references working on prey-predator model, in which they used classical control schemes with a very long and complicated steps. While the proposed method of this paper simplifies the work steps. Numerical simulation results are presented to validate the theoretical analysis.

Multitemporal landslide inventory and susceptibility map for the Arun River Basin, Nepal

AbstractThe transboundary Arun River Basin (ARB) spreads across Nepal and Tibet. Nearly 95% of the basin lies in Tibet through which the Pumqu River flows, forming the Arun River once it enters Nepal. The ARB has five large hydropower projects undergoing construction or planned for the future. Rainfall and earthquake‐induced landslides, landslide‐dammed lakes and landslide‐induced glacial lake outburst floods pose major risks to smooth operation of these projects. To safeguard upcoming hydropower projects, areas susceptible to landslides in the ARB must be identified. We used high‐resolution satellite imagery and open‐source tools to generate a multitemporal landslide inventory for the basin. The rigorously quality‐controlled inventory represents a yearly record of landslides from 2011 to 2020. A data‐driven approach was used to map areas susceptible to landslides within the ARB. The multitemporal landslide inventory combined with other readily available Earth observation‐based variables was used to create a landslide susceptibility map. The susceptibility analysis provides a valuable initial estimate of where landslides are likely to initiate. These landslide products could form the basis of more comprehensive local studies to inform hydropower project development.

The genetic and environmental variance of radial increment in Scots pine of south-eastern Baltic provenances in response to weather extremes

Intensification of weather anomalies, particularly those related to temperature in warming winters and moisture availability, have been identified as the major emerging climatic threats to forest ecosystems in the hemiboreal zone. Considering the large-scale nature of the threats, assisted migration and tree breeding appear as the most promising means for mitigating the climatic risks. However, for successful implementation of such means, information on the genetic control over the weather sensitivity of trees is needed. Local genetic adaptations of populations occur to maximize competitiveness and survival, while the differences in phenotypic plasticity, implying varying genotype by environmental interactions, can be utilized for the acquisition of locally targeted reproductive material. To gain initial (rough) estimates of genetic control and phenotypic plasticity of growth responses to weather anomalies, a set of seven native eastern Baltic provenances differing by productivity in five trials in Latvia and northern Germany were studied. Tree-ring widths were measured for 10–15 trees per provenance per trial. Relative growth changes and pointer year values were calculated to link changes in increment with weather anomalies and to estimate heritability on an annual basis by the methods of quantitative genetics. During the analysed period (1987–2017), four to seven trial- and provenance-specific pointer years (common relative growth changes) were estimated, which were mainly triggered by co-occurring anomalies in moisture availability and winter thermal regime. This implied resilience of the studied trees to singular weather anomalies, suggesting their adaptability. Furthermore, the heritability estimates peaked one to two years after the pointer years, implying that growth recovery and hence resilience rather than resistance was genetically controlled. Still, local variability of pointer years and heritability estimates portrayed explicit phenotypic plasticity of responses, implying the potential for breeding to locally improve weather tolerance of growth. Keywords: Pinus sylvestris; local adaptation; phenotypic plasticity; growth recovery; tree-ring width; pointer years

Hybrid model for wind power estimation based on BIGRU network and error discrimination‐correction

AbstractAccurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. This paper proposes a novel approach to enhance the accuracy of wind power estimation through a hybrid model integrating neural networks and error discrimination‐correction techniques. In order to improve the accuracy of estimation, a bidirectional gating recurrent unit is developed, forming an initial wind power estimation curve through training. Additionally, a sequential model‐based algorithmic configuration optimizes bidirectional gating recurrent unit's network hyperparameters. To tackle estimation errors, a multi‐layer perceptron combined with sequential model‐based algorithmic configuration is employed to create a classification model that automatically discerns the quality of estimates. Subsequently, an innovative correction model, based on grey relevancy degree and relevancy errors, is devised to rectify erroneous estimates. The final estimates result from a summation of the initial estimates and the values derived from error corrections. By analysing the real data from a wind farm in northwest China, a simulation test validates the proposed hybrid model. Experimental results demonstrate a substantial improvement in modelling accuracy when compared to the initial model.