• Kyungpook Mathematical Journal
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• v.59 no.2
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• pp.301-314
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• 2019

The aim of this article is to make a connection between the Pascal distribution series and some subclasses of normalized analytic functions whose coefficients are probabilities of the Pascal distribution. For these functions, for linear combinations of these functions and their derivatives, for operators defined by convolution products, and for the Alexander-type integral operator, we find simple sufficient conditions such that these mapping belong to a general class of functions defined and studied by Goodman, Rønning, and Bharati et al.

• Kyungpook Mathematical Journal
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• v.61 no.1
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• pp.99-110
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• 2021

In the present paper, we determine new characterisations of the subclasses ����∗��(α, β; γ) and ������(α, β; γ) of analytic functions associated with Pascal distribution series ${\Phi}^m_q(z)=z-{\sum_{n=2}^{\infty}}(^{n+m-2}_{m-1})q^{n-1}(1-q)^mz^n$. Further, we give necessary and sufficient conditions for an integral operator related to Pascal distribution series ${\mathcal{G}}^m_qf(z)={\int_{0}^{z}}{\frac{{\Phi}^m_q(t)}{t}}dt$ to belong to the above classes. Several corollaries and consequences of the main results are also considered.

• Nonlinear Functional Analysis and Applications
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• v.27 no.1
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• pp.99-110
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• 2022

The main object of this paper is to provide necessary and sufficient conditions for the generalized Struve functions of first kind to be in the classes 𝒮(k, λ) and 𝒞(k, λ). Furthermore, we give conditions for the integral operator 𝓛(m, c, z) = ∫^z₀(2 - u_p(t))dt to be in the class 𝒞^*(k, λ). Several corollaries and consequences of the main results are also considered.

• Journal of Applied and Pure Mathematics
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• v.4 no.1_2
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• pp.9-26
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• 2022

The purpose of this work is to study the existence and continuous dependence on neutral stochastic partial integrodifferential equations with impulsive effects, perturbed by a fractional Brownian motion with Hurst parameter $H{\in}({\frac{1}{2}},\;1)$. We use the theory of resolvent operators developed in Grimmer [19] to show the existence of mild solutions. Further, we establish a new impulsive-integral inequality to prove the exponential stability of mild solutions in the mean square moment. Finally, an example is presented to illustrate our obtained results.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.272-276
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• 2004

The conventional PID (Proportional-Integral-Derivative) control technique is widely used for the process control in many industries since it is simple in structure and provides the good response. Nowadays, this control technique has been developed on the Programmable Logic Controller (PLC) to use for the process control loop. However, using this technique is difficult when tuning the PID parameters ($K_p$, $T_i$ and $T_d$) to achieve the best response. Moreover, trial-and-error procedure along with the operator experiences are required to obtain the best results when tuning the PID controller parameters. This paper proposes the self-tuning PID controller based on PLC for the process control in the industries. The proposed self-tuning PID controller uses the PLC-based PID structures to control the process production. The proposed PID tuning utilizes the PLC to synthesize and analyze controller parameter as well as to tune for appropriate parameters using Dahlin method and extrapolation. Experimental results using a self-tuning PID controller to control temperature of the oven show that the controller developed is capable of controlling the process very effectively and provides a good response.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.639-650
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• 2008

Electricity price forecasting has become an integral part of power system operation and control. In this paper, a wavelet transform (WT) based neural network (NN) model to forecast price profile in a deregulated electricity market has been presented. The historical price data has been decomposed into wavelet domain constitutive sub series using WT and then combined with the other time domain variables to form the set of input variables for the proposed forecasting model. The behavior of the wavelet domain constitutive series has been studied based on statistical analysis. It has been observed that forecasting accuracy can be improved by the use of WT in a forecasting model. Multi-scale analysis from one to seven levels of decomposition has been performed and the empirical evidence suggests that accuracy improvement is highest at third level of decomposition. Forecasting performance of the proposed model has been compared with (i) a heuristic technique, (ii) a simulation model used by Ontario's Independent Electricity System Operator (IESO), (iii) a Multiple Linear Regression (MLR) model, (iv) NN model, (v) Auto Regressive Integrated Moving Average (ARIMA) model, (vi) Dynamic Regression (DR) model, and (vii) Transfer Function (TF) model. Forecasting results show that the performance of the proposed WT based NN model is satisfactory and it can be used by the participants to respond properly as it predicts price before closing of window for submission of initial bids.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.4
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• pp.82-92
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• 1997

In this paper, a fuzzy measure and integral-based model fnr interactive systems is proposed. The processes of model identification consists of the following three steps : (i) structure identification (ii) parameter identification and (iii) selection of an optimal model. An algorithm for the model structure identification using the well-known genetic algorithm ((;A) with a modified selection operator is proposed. A method for the identification of par;imetcrs corresponding to fuzzy measures is presented. A statistical model selection criterion is used for the selection of an optimal model among the candidates. Finally, experimental results obtained hy applying the proposed model to the subjective evaluation data set and the well-known time series data are presented to show the validity of the proposed model.

• Journal of the Korean Mathematical Society
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• v.33 no.4
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• pp.823-855
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• 1996

We study Dirichlet forms and the associated diffusion processes for the Gibbs measures related to the quantum unbounded spin systems (lattice boson systems) interacting via superstable and regular potentials. This work is a continuation of the author's previous study on the classical systems [LPY] to the quantum cases. In [LPY], we constructed Dirichlet forms and the associated diffusion processes for the Gibbs measures of classical unbounded spin systems. Furthermore, we also showed the essential self-adjointness of the Dirichlet operator and the log-Sobolev inequality for any Gibbs measure under appropriate conditions on the potentials. In this atudy we try to extend the results of the classical systems to the quantum cases. Because of some technical difficulties, we are only able to construct a Dirichlet form and the associated diffusion process for any Gibbs measure of the quantum systems. We utilize the general scheme of the previous work on the theory in infinite dimensional spaces [AH-K1-2, AKR, AR1-2, Kus, MR, Ro, Sch] and the ideas we employed in our study of the calssical systems ]LPY].

• Journal of Korean Society for Quality Management
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• v.21 no.2
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• pp.1-16
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• 1993

Early generations of products had little to no inherent capability to test themselves. The technologies involved often required only visual inspection and limited probing to troubleshoot the system once it was turned over to maintenance personnel. However, as the complexity of military and commercial systems grew, symptoms of failure became less noticeable to the operator. Therefore, the procedure to access, inspect, repair and replace a component became complicated, the requirements for personnel skill and testing equipment increased. and it took too long of a time to maintain a system. Meanwhile, the need for availability became more mission-critical and maintenance become very expensive. The obvious solution was to design in-system circuits or devices to self-test the primary system, the Built-In-Test(BIT) was born. This approach has continued right on up through present systems and is an integral part of systems now being designed. The object of this paper is to present a state-of-the-art research for filtering out the BIT diagnosis mistakes using Bayesian analysis and develop the algorithm for Redundant systems with BIT to improve BIT diagnosis.

• Journal of Advanced Marine Engineering and Technology
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• v.30 no.7
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• pp.791-799
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• 2006

The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.