Wind Power Forecasting Methods Based on Deep Learning: A Survey

Accurate wind power forecasting in wind farm can effectively reduce the enormous impact on grid operation safety when high permeability intermittent power supply is connected to the power grid. Aiming to provide reference strategies for relevant researchers as well as practical applications, this paper attempts to provide the literature investigation and methods analysis of deep learning, enforcement learning and transfer learning in wind speed and wind power forecasting modeling. Usually, wind speed and wind power forecasting around a wind farm requires the calculation of the next moment of the definite state, which is usually achieved based on the state of the atmosphere that encompasses nearby atmospheric pressure, temperature, roughness, and obstacles. As an effective method of high-dimensional feature extraction, deep neural network can theoretically deal with arbitrary nonlinear transformation through proper structural design, such as adding noise to outputs, evolutionary learning used to optimize hidden layer weights, optimize the objective function so as to save information that can improve the output accuracy while filter out the irrelevant or less affected information for forecasting. The establishment of high-precision wind speed and wind power forecasting models is always a challenge due to the randomness, instantaneity and seasonal characteristics

Image Segmentation Based on Mathematical Morphological Operator

Image segmentation is the process of partitioning a digital image into multiple regions (sets of pixels); the pixels in each region have similar attributes. It is often used to separate an image into regions in terms of surfaces, objects, and scenes, especially for object location and boundary extraction. Until now, many general-purpose algorithms and techniques have been proposed for image segmentation. Typical and traditional methods are: (1) threshold-based method; (2) edge-based method; and (3) region-based method. In this chapter, we propose an approach of image segmentation based on mathematical morphology operator: toggle operator. The experimental result shows that the proposed method can segment natural scene images into homogeneous regions effectively

The trend of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in spontaneous intracerebral hemorrhage and the predictive value of short-term postoperative prognosis in patients

BackgroundNeutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) play an important role in the inflammatory response in various diseases, but the role in the course of spontaneous intracerebral hemorrhage (ICH) is unclear.MethodsThis study retrospectively collected baseline characteristics and laboratory findings, including NLR and PLR at different time points, from spontaneous ICH patients undergoing surgery between January 2016 and June 2021. Patients were scored using the modified Rankin Scale (mRS) to evaluate their functional status at 30 days post-operation. Patients with mRS score ≥3 were defined as poor functional status, and mRS score <3 was defined as good functional status. The NLR and PLR were calculated at admission, 48 h after surgery and 3–7 days after surgery, respectively, and their trends were observed by connecting the NLR and PLR at different time points. Multivariate logistic regression analysis was used to identify independent risk factors affecting the prognosis of ICH patients at 30 days after surgery.ResultsA total of 101 patients were included in this study, and 59 patients had a poor outcome at 30 days after surgery. NLR and PLR gradually increased and then decreased, peaking at 48 h after surgery. Univariate analysis demonstrated that admission Glasgow Coma Scale (GCS) score, interval from onset to admission, hematoma location, NLR within 48 h after surgery and PLR within 48 h after surgery were associated with poor 30-day prognosis. In multivariate logistic regression analysis, NLR within 48 h after surgery (OR, 1.147; 95% CI, 1.005, 1.308; P, 0.042) was an independent risk factor for 30-day after surgery prognosis in spontaneous ICH patients.ConclusionIn the course of spontaneous intracerebral hemorrhage, NLR and PLR initially increased and subsequently decreased, reaching their peak values at 48 h after surgery. High NLR within 48 h after surgery was an independent risk factor for poor prognosis 30 days after surgery in spontaneous ICH patients

Design and implementation of multivariable cooperative control and failure accommodation

A mechanical system designed for precise positioning usually consists of many individually actuated subsystems. Redundancy and diversity properties of subsystems are used in the design of a reconfigurable control scheme to achieve optimal coordination and fault accommodation. This dissertation introduces a general procedure of synthesizing multivariable control algorithms that utilize the redundancy and diversity of the subsystems, and discussed the related controller design and implementation issues through three applications with different emphases. A robot target tracking system is employed to demonstrate that the subsystems with different talents work cooperatively towards the same objective. The tracking controller also has the ability to instruct the remaining healthy subsystems to achieve fault accommodation when failure occurs. For each fault scenario only one fixed accommodation controller is needed to address a variety of mechanical and electrical failure conditions. A hard drive dual-stage actuator servo control application illustrates the synthesis of cooperative systems where the participation of each subsystem needs to be adjusted and their limitations accommodated. This dissertation also discusses the implementation of designed digital tracking controllers using embedded microprocessor. A spinning vehicle maneuver control project exemplifies the design process from system modeling to control synthesis and implementation on DSP microprocessor circuits. The discussion on the designed sinusoidal tracking controller’s robustness against command frequency variation and other practical issues arising in the implementation are also included.Ph.D., Mechanical Engineering -- Drexel University, 200

Design and implementation of multivariable cooperative control and failure accommodation

A mechanical system designed for precise positioning usually consists of many individually actuated subsystems. Redundancy and diversity properties of subsystems are used in the design of a reconfigurable control scheme to achieve optimal coordination and fault accommodation. This dissertation introduces a general procedure of synthesizing multivariable control algorithms that utilize the redundancy and diversity of the subsystems, and discussed the related controller design and implementation issues through three applications with different emphases. A robot target tracking system is employed to demonstrate that the subsystems with different talents work cooperatively towards the same objective. The tracking controller also has the ability to instruct the remaining healthy subsystems to achieve fault accommodation when failure occurs. For each fault scenario only one fixed accommodation controller is needed to address a variety of mechanical and electrical failure conditions. A hard drive dual-stage actuator servo control application illustrates the synthesis of cooperative systems where the participation of each subsystem needs to be adjusted and their limitations accommodated. This dissertation also discusses the implementation of designed digital tracking controllers using embedded microprocessor. A spinning vehicle maneuver control project exemplifies the design process from system modeling to control synthesis and implementation on DSP microprocessor circuits. The discussion on the designed sinusoidal tracking controller’s robustness against command frequency variation and other practical issues arising in the implementation are also included.Ph.D., Mechanical Engineering -- Drexel University, 200

Multivariable controller design for hard drive dual-stage actuator servo systems

Paper presented at the 2005 IEEE International Conference on Mechatronics, Taipei, Taiwan.A multivariable multi-objective approach has been presented for the design of servo controller for a dual-stage actuator system. The designed control algorithm instructs the two actuators to cooperate towards a faster track seeking and better disturbance rejection than any actuator acting alone. Cooperation is explicitly formulated as control objectives and the optimal control algorithm is designed using the H2 control theory and regulator theory. Each actuator's involvement in the cooperation can be further adjusted by changing the design weighting coefficients, while the design procedure guarantees the stability of the control system

Chemical Genomics Approach Leads to the Identification of Hesperadin, an Aurora B Kinase Inhibitor, as a Broad-Spectrum Influenza Antiviral

Influenza viruses are respiratory pathogens that are responsible for annual influenza epidemics and sporadic influenza pandemics. Oseltamivir (Tamiflu((R))) is currently the only FDA-approved oral drug that is available for the prevention and treatment of influenza virus infection. However, its narrow therapeutic window, coupled with the increasing incidence of drug resistance, calls for the next generation of influenza antivirals. In this study, we discovered hesperadin, an aurora B kinase inhibitor, as a broad-spectrum influenza antiviral through forward chemical genomics screening. Hesperadin inhibits multiple human clinical isolates of influenza A and B viruses with single to submicromolar efficacy, including oseltamivir-resistant strains. Mechanistic studies revealed that hesperadin inhibits the early stage of viral replication by delaying the nuclear entry of viral ribonucleoprotein complex, thereby inhibiting viral RNA transcription and translation as well as viral protein synthesis. Moreover, a combination of hesperadin with oseltamivir shows synergistic antiviral activity, therefore hesperadin can be used either alone to treat infections by oseltamivir-resistant influenza viruses or used in combination with oseltamivir to delay resistance evolution among oseltamivir-sensitive strains. In summary, the discovery of hesperadin as a broad-spectrum influenza antiviral offers an alternative to combat future influenza epidemics and pandemics.University of Arizona; NIH [AI 119187, T32 GM008804]Open Access Journal.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]