In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taki...
In this paper, the accuracy of soft computing technique in solar radiation prediction based on series of measured meteorological data (monthly mean sunshine duration, monthly mean maximum and minimum temperature) taking from Iseyin meteorological station in Nigeria was examined. The process, which simulates the solar radiation with support vector regression (SVR), was constructed. The inputs were monthly mean maximum temperature (Tmax), monthly mean minimum temperature (Tmin) and monthly mean sunshine duration ( $$ \bar{n} $$ ). Polynomial and radial basis functions (RBF) are applied as the SVR kernel function to estimate solar radiation. According to the results, a greater improvement in estimation accuracy can be achieved through the SVR with polynomial basis function compared to RBF. The SVR coefficient of determination R 2 with the polynomial function was 0.7395 and with the radial basis function, the R 2 was 0.5877.
Modern societies increasingly rely on automatic controlsystems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social compon...
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Modern societies increasingly rely on automatic controlsystems. These systems are hardly pure technical systems; instead they are complex socio-technical systems, which consist of technical elements and social components. It is necessary to have a systematic approach to analyze these systems because it is growing evidence that accidents from these systems usually have complex causal factors which form an interconnected network of events,rather than a simple cause-effect chain. We take railway Train controlsystems(TCS) as an example to demonstrate the importance of the socio-technical approach to analyze the system. The paper presents an investigation of recent high-speed railway accident by applying STAMP – one of the most notable socio-technical system analysis techniques, outlines improvements to the system which could avoid similar accidents in the future. We also provide our valuable feedback for the use of STAMP.
This paper presents a vision-based fingertip writing digits detection and recognition system using a CMOS camera and FPGA implementation. It is a real-time signature detector, since the image process algorithms are al...
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This paper presents a vision-based fingertip writing digits detection and recognition system using a CMOS camera and FPGA implementation. It is a real-time signature detector, since the image process algorithms are all executed in Verilog code. The experimental results show that the system can successfully recognize fingertip-numeral-writing with a accuracy rate of 95.8%.
In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel lear...
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In this paper, we present a new framework for large scale online kernel learning, making kernel methods efficient and scalable for large-scale online learning applications. Unlike the regular budget online kernel learning scheme that usually uses some budget maintenance strategies to bound the number of support vectors, our framework explores a completely different approach of kernel functional approximation techniques to make the subsequent online learning task efficient and scalable. Specifically, we present two different online kernel machine learning algorithms: (i) Fourier Online Gradient Descent (FOGD) algorithm that applies the random Fourier features for approximating kernel functions; and (ii) Nyström Online Gradient Descent (NOGD) algorithm that applies the Nyström method to approximate large kernel matrices. We explore these two approaches to tackle three online learning tasks: binary classification, multi-class classification, and regression. The encouraging results of our experiments on large-scale datasets validate the effectiveness and efficiency of the proposed algorithms, making them potentially more practical than the family of existing budget online kernel learning approaches.
This paper proposes a statistical method for no-reference image quality assessment using steerable pyramid decomposition without any prior knowledge about the distortions of the original image. Because the means of (l...
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In this paper,we provide a unified expression to obtain the conditions on the restricted isometry constantδ2s(Φ).These conditions cover the important results proposed by Candes et *** each of them is a sufficient co...
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In this paper,we provide a unified expression to obtain the conditions on the restricted isometry constantδ2s(Φ).These conditions cover the important results proposed by Candes et *** each of them is a sufficient condition for sparse signal *** the noiseless case,whenδ2s(Φ)satisfies any one of these conditions,the s-sparse signal can be exactly recovered via(l1)constrained minimization.
Group role assignment with a flexible formation (GRAFF) is essential for group performance optimization in collaborative systems. In this paper, problems of GRAFF are formalized based on the Environment-Class, Agent, ...
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Traditional anti-windup compensators are designed for activation immediately at the occurrence of actuator ***,anti-windup compensators were designed for actuation either after the saturation has reached a certain lev...
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Traditional anti-windup compensators are designed for activation immediately at the occurrence of actuator ***,anti-windup compensators were designed for actuation either after the saturation has reached a certain level or in anticipation of its *** the case of static anti-windup compensators,it has been shown that an anti-windup compensator designed for activation in anticipation of actuator saturation would lead to better performance than those designed for immediate or delayed activation could,both in terms of transient performance and the size of the domain of *** recently,it has been shown that a dynamic anti-windup compensator designed for anticipatory activation would also result in better transient performance than those designed for immediate or delayed activation *** this paper,we design dynamic anti-windup compensators for the enlargement of the domain of *** compensators are designed respectively for immediate,delayed and anticipatory *** will show by simulation that a dynamic anti-windup compensator designed for anticipatory activation would result in a larger domain of attraction than a dynamic anti-windup compensator designed for immediate or delayed activation could.
Furnace exit gas temperature(FEGT) is the key parameter in the furnace ash fouling monitoring system. Since the standard least squares support vector machine(LSSVM) is not suitable for online identification and contro...
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ISBN:
(纸本)9781479947249
Furnace exit gas temperature(FEGT) is the key parameter in the furnace ash fouling monitoring system. Since the standard least squares support vector machine(LSSVM) is not suitable for online identification and control of FEGT,a novel CM-LSSVM-PLS method is proposed to predict FEGT in this paper. In the process of CM-LSSVM-PLS method, c-means cluster(CM) algorithm is used to partition the training data into several different subsets by considering the characteristics of operational data. Submodels are subsequently developed in the individual subsets based on LSSVM method. Partial least squares algorithm(PLS) is employed as the combination strategy. The online updating algorithm is then applied to the CM-LSSVM-PLS model. The proposed online model is verified through operation data of a 300 MW generating unit. The simulation results show that the proposed online updating model is effective for online FEGT forecasting.
This paper mainly discusses the remote tracking problem with partly quantized information and packet-dropout. Since the network exists between the remote plant and the local plant, any information transmitted between ...
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ISBN:
(纸本)9781479947249
This paper mainly discusses the remote tracking problem with partly quantized information and packet-dropout. Since the network exists between the remote plant and the local plant, any information transmitted between each other will experience the quantization errors and may be lost. In this situation, the controller of the local system needs to consider both the exact local information and the inaccurate remote information. A state feedback controller is adopted and the theorems to design such controller are given in terms of bilinear matrix inequalities(BMIs). Moreover, an algorithm is proposed and these BMIs are converted into a convex optimization problem. Finally, the efficiency of the proposed method is demonstrated by a simulation example.
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