DiffLoad: Uncertainty Quantification in Load Forecasting with Diffusion Model

Electrical load forecasting is of great significance for the decision makings in power systems, such as unit commitment and energy management. In recent years, various self-supervised neural network-based methods have been applied to electrical load forecasting to improve forecasting accuracy and capture uncertainties. However, most current methods are based on Gaussian likelihood methods, which aim to accurately estimate the distribution expectation under a given covariate. This kind of approach is difficult to adapt to situations where temporal data has a distribution shift and outliers. In this paper, we propose a diffusion-based Seq2seq structure to estimate epistemic uncertainty and use the robust additive Cauchy distribution to estimate aleatoric uncertainty. Rather than accurately forecasting conditional expectations, we demonstrate our method's ability in separating two types of uncertainties and dealing with the mutant scenarios

Benchmarks and Custom Package for Electrical Load Forecasting

Load forecasting is of great significance in the power industry as it can provide a reference for subsequent tasks such as power grid dispatch, thus bringing huge economic benefits. However, there are many differences between load forecasting and traditional time series forecasting. On the one hand, load forecasting aims to minimize the cost of subsequent tasks such as power grid dispatch, rather than simply pursuing prediction accuracy. On the other hand, the load is largely influenced by many external factors, such as temperature or calendar variables. In addition, the scale of predictions (such as building-level loads and aggregated-level loads) can also significantly impact the predicted results. In this paper, we provide a comprehensive load forecasting archive, which includes load domain-specific feature engineering to help forecasting models better model load data. In addition, different from the traditional loss function which only aims for accuracy, we also provide a method to customize the loss function based on the forecasting error, integrating it into our forecasting framework. Based on this, we conducted extensive experiments on load data at different levels, providing a reference for researchers to compare different load forecasting models

Optimization of volume fracturing technology for shallow bow horizontal well in a tight sandstone oil reservoir

The physical property of Chang 6 reservoir in Yanchang oilfield is poor, and the heterogeneity is strong. Multistage fracturing of horizontal wells is easy to form only one large horizontal fracture, but it is difficult to control the fracture height and length. The new mining method of “bow horizontal well + multistage horizontal joint” can effectively increase the multistage horizontal joint’s spatial position, which improves the drainage area and stimulation efficiency of oil wells. Due to the reservoir’s low permeability and strong heterogeneity, the single well mode of “bow horizontal well + multistage horizontal fracture” cannot effectively produce Chang 6 reservoir. To improve the production degree of the g 6 reservoir, the fracture model is established using equivalent conductivity and the multigrid method. The pressure response functions of horizontal wells and volume fracturing horizontal wells are established by using the source function, and the relationship between reservoir permeability and starting pressure gradient in the block is calculated. On this basis, the reservoir productivity equation of the block is established, which provides a basis for optimizing the fracturing design parameters of horizontal wells. It is proposed that the flow unit should be considered in the design of fracturing parameters of horizontal fractures, the number of fractures should comprehensively consider whether the fractures can make each flow unit be used, and have large controlled reserves, and the scale of fracturing should comprehensively consider the output and cost. The fracture network model is established by using equivalent conductivity and multi-gridthod, and the volume fracturing design parameters of horizontal wells are optimized, considering the seepage characteristics of the flow unit. The fracturing design parameters of the horizontal section are further defined, which provides a theoretical basis for the efficient development of shallow tight reservoirs

Convergence Analysis of Semi-Implicit Euler Methods for Solving Stochastic Age-Dependent Capital System with Variable Delays and Random Jump Magnitudes

We consider semi-implicit Euler methods for stochastic age-dependent capital system with variable delays and random jump magnitudes, and investigate the convergence of the numerical approximation. It is proved that the numerical approximate solutions converge to the analytical solutions in the mean-square sense under given conditions

Coherent Time-Varying Graph Drawing with Multifocus+Context Interaction

Abstract—We present a new approach for time-varying graph drawing that achieves both spatiotemporal coherence and multifocus+context visualization in a single framework. Our approach utilizes existing graph layout algorithms to produce the initial graph layout, and formulates the problem of generating coherent time-varying graph visualization with the focus+context capability as a specially-tailored deformation optimization problem. We adopt the concept of the super graph to maintain spatiotemporal coherence and further balance the needs for aesthetic quality and dynamic stability when interacting with time-varying graphs through focus+context visualization. Our method is particularly useful for multifocus+context visualization of time-varying graphs where we can preserve the mental map by preventing nodes in the focus from undergoing abrupt changes in size and location in the time sequence. Experiments demonstrate that our method strikes a good balance between maintaining spatiotemporal coherence and accentuating visual foci, thus providing a more engaging viewing experience for the users. Index Terms—Graph drawing, time-varying graphs, spatiotemporal coherence, focus+context visualization

Prevalence and related factors of epilepsy in children and adolescents with cerebral palsy: a systematic review and meta-analysis

Objective: To study the worldwide prevalence and associated factors of epilepsy in children and adolescents with Cerebral Palsy (CP) and to analyze the differences between various subgroups. Method: We identified all potential studies on the prevalence of epilepsy in children and adolescents with CP from PubMed, Web of Science, and Embase. The search time was from the establishment of the database to November 2022. Randomized effects meta-analysis models were used to calculate the prevalence of epilepsy in CP. Subgroup analysis and meta-regression were utilized to further explore heterogeneity between articles and prevalence disparities between subgroups. The funnel plot and Egger’s test were used to investigate potential publication bias. Results: Seventy-two articles, comprising 53,969 children and adolescents with CP, were included in this study. The results indicated a total epilepsy prevalence of 38.0% (95% CI: 34.8%–41.2%) in CP. The prevalence of epilepsy was 46.4% (95% CI: 41.4%–51.5%) in clinical sample-based studies and 31.6% (95% CI: 28.7%–34.5%) in population-based studies. Meta-regression demonstrated that the sample source, neonatal seizure, family history of epilepsy, EEG or cranial imaging abnormalities, intellectual/cognitive impairment, and topographical types of CP were heterogeneous contributors to the epilepsy prevalence in CP. Conclusion: Approximately one-third of children and adolescents with CP have epilepsy, and the sample source can significantly impact the total prevalence of epilepsy. Neonatal seizures, family history of epilepsy, EEG abnormalities, cranial imaging abnormalities, severe intellectual disability, and quadriplegia may be contributing factors to epilepsy comorbid in CP. Further study is required to verify the strength of these associations with epilepsy. This study aids in identifying the clinical characteristics of young people with CP at risk of developing epilepsy, which may assist clinicians in the early prevention and diagnosis of epilepsy within this population