Critical chain construction with multi-resource constraints based on portfolio technology in South-to-North Water Diversion Project

Recently, the critical chain study has become a hot issue in the project management research field. The construction of the critical chain with multi-resource constraints is a new research subject. According to the system analysis theory and project portfolio theory, this paper discusses the creation of project portfolios based on the similarity principle and gives the definition of priority in multi-resource allocation based on quantitative analysis. A model with multi-resource constraints, which can be applied to the critical chain construction of the A-bid section in the South-to-North Water Diversion Project, was proposed. Contrast analysis with the comprehensive treatment construction method and aggressive treatment construction method was carried out. This paper also makes suggestions for further research directions and subjects, which will be useful in improving the theories in relevant research fields.

Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

Since its inception,the Internet has been rapidly evolving.With the advancement of science and technology and the explosive growth of the population,the demand for the Internet has been on the rise.Many applications in education,healthcare,entertainment,science,and more are being increasingly deployed based on the internet.Concurrently,malicious threats on the internet are on the rise as well.Distributed Denial of Service(DDoS)attacks are among the most common and dangerous threats on the internet today.The scale and complexity of DDoS attacks are constantly growing.Intrusion Detection Systems(IDS)have been deployed and have demonstrated their effectiveness in defense against those threats.In addition,the research of Machine Learning(ML)and Deep Learning(DL)in IDS has gained effective results and significant attention.However,one of the challenges when applying ML and DL techniques in intrusion detection is the identification of unknown attacks.These attacks,which are not encountered during the system’s training,can lead to misclassification with significant errors.In this research,we focused on addressing the issue of Unknown Attack Detection,combining two methods:Spatial Location Constraint Prototype Loss(SLCPL)and Fuzzy C-Means(FCM).With the proposed method,we achieved promising results compared to traditional methods.The proposed method demonstrates a very high accuracy of up to 99.8%with a low false positive rate for known attacks on the Intrusion Detection Evaluation Dataset(CICIDS2017)dataset.Particularly,the accuracy is also very high,reaching 99.7%,and the precision goes up to 99.9%for unknown DDoS attacks on the DDoS Evaluation Dataset(CICDDoS2019)dataset.The success of the proposed method is due to the combination of SLCPL,an advanced Open-Set Recognition(OSR)technique,and FCM,a traditional yet highly applicable clustering technique.This has yielded a novel method in the field of unknown attack detection.This further expands the trend of applying DL and ML techniques in the development of intrusion detection systems and cybersecurity.Finally,implementing the proposed method in real-world systems can enhance the security capabilities against increasingly complex threats on computer networks.

Robust Fuzzy Tracking Control for Nonlinear Networked Control Systems with Integral Quadratic Constraints

This paper investigates the robust tracking control problcm for a class of nonlinear networked control systems （NCSs） using the Takagi-Sugeno （T-S） fuzzy model approach. Based on a time-varying delay system transformed from the NCSs, an augmented Lyapunov function containing more useful information is constructed. A less conservative sufficient condition is established such that the closed-loop systems stability and time-domain integral quadratic constraints （IQCs） are satisfied while both time-varying network- induced delays and packet losses are taken into account. The fuzzy tracking controllers design scheme is derived in terms of linear matrix inequalities （LMIs） and parallel distributed compensation （PDC）. Furthermore, robust stabilization criterion for nonlinear NCSs is given as an extension of the tracking control result. Finally, numerical simulations are provided to illustrate the effectiveness and merits of the proposed method.

Integrated guidance and control of guided projectile with multiple constraints based on fuzzy adaptive and dynamic surface

Based on fuzzy adaptive and dynamic surface(FADS),an integrated guidance and control(IGC)approach was proposed for large caliber naval gun guided projectile,which was robust to target maneuver,canard dynamic characteristics,and multiple constraints,such as impact angle,limited measurement of line of sight(LOS)angle rate and nonlinear saturation of canard deflection.Initially,a strict feedback cascade model of IGC in longitudinal plane was established,and extended state observer(ESO)was designed to estimate LOS angle rate and uncertain disturbances with unknown boundary inside and outside of system,including aerodynamic parameters perturbation,target maneuver and model errors.Secondly,aiming at zeroing LOS angle tracking error and LOS angle rate in finite time,a nonsingular terminal sliding mode(NTSM)was designed with adaptive exponential reaching law.Furthermore,combining with dynamic surface,which prevented the complex differential of virtual control laws,the fuzzy adaptive systems were designed to approximate observation errors of uncertain disturbances and to reduce chatter of control law.Finally,the adaptive Nussbaum gain function was introduced to compensate nonlinear saturation of canard deflection.The LOS angle tracking error and LOS angle rate were convergent in finite time and whole system states were uniform ultimately bounded,rigorously proven by Lyapunov stability theory.Hardware-in-the-loop simulation(HILS)and digital simulation experiments both showed FADS provided guided projectile with good guidance performance while striking targets with different maneuvering forms.

Multi-objective linear fractional inventory model with possibility and necessity constraints under generalised intuitionistic fuzzy set environment

This study presented a multi-objective linear fractional inventory (LFI) problem with generalised intuitionistic fuzzy numbers. In modelling, the authors have assumed the ambiances where generalised trapezoidal intuitionistic fuzzy numbers (GTIFNs) used to handle the uncertain information in the data. Then, the given multi-objective generalised intuitionistic fuzzy LFI model was transformed into its equivalent deterministic linear fractional programming problem by employing the possibility and necessity measures. Finally, the applicability of the model is demonstrated with a numerical example and the sensitivity analysis under several parameters is investigated to explore the study.

约束中具有Fuzzy参数的多目标规划(Ⅰ)——解的定义及其性质

考察了约束函数中具有Fuzzy参数的多目标规划 (FPVP) ,首先引进Fuzzy集来描述 (FPVP)的约束 ,然后给出α-拟有效解 ,α -有效解的定义并讨论了其基本性质 ,最后举例说明本文的解与 [2

FUZZY COORDINATION AND FORCE/POSITION CONTROL OF ROBOTIC MANIPULATOR

It is crucial for implementing force/position control of robotic manipulator under the constraint of unknown environment to determine the force control and the position control directions. This paper presents an on line algorithm to real timely estimate the tangent and the normal vectors of the constraint surface based on the measured contact force under the consideration of frictional force. A fuzzy synthesis policy is proposed to coordinate the conflict between the compliant force control and the stiff position control. An experimental study on an AdeptThree, a SCARA type robotic manipulator, is conducted. The experimental results show that the policy presented in the paper is effective.

Fuzzy数学规划求解的约束域分割法

对模糊数学规划的目标函数取大∨与取小∧的问题，给出了一种求解方法——约束域分割法，此法对约束集凹集的数学规划问题亦有效。

集成TOC/TRIZ/Fuzzy的产品概念设计方法的研究

为有效的完成产品概念设计,提出了一种基于约束理论、创造性解决问题方法和模糊评价理论集成的产品概念设计模型。该模型用约束理论发现影响产品的主要矛盾,利用创造新解决问题理论找到问题的通用解决办法,最后,结合模糊评价理论分析出该问题的最优解。并采用了一个番茄输送带的应用实例来验证该方法的有效性。

约束函数中含有Fuzzy参数的多目标规划(Ⅱ)——约束集及其象集的性质

用Fuzzy集刻画约束函数中含有Fuzzy参数的多目标规划的约束集,讨论它及其象集的性质。本文的全部结果是研究α-有效解的存在性及导出算法所必需的。

Constrained predictive control based on T-S fuzzy model for nonlinear systems

A constrained generalized predictive control （GPC） algorithm based on the T-S fuzzy model is presented for the nonlinear system. First, a Takagi-Sugeno （T-S） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. Since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this T-S fuzzy model, a GPC algorithm with input constraints is presented. This strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. So it needs only a small computer memory and the computational speed is high. The simulation results show a good performance for the nonlinear systems.

FUZZY RELIABILITY-BASED OPTIMUM DESIGN OF LAMINATED COMPOSITES

In conventional reliability-based optimum design of structures, the reliability is computed based on the probability assumption, and the design objective and constraint are considered as deterministic ones. In many cases, however, there exist some fuzzy factors in the design objective and constraint functions. In this paper, the fuzzy reliability and fuzzy constraint are introduced to establish the fuzzy reliability-based optimum model for laminated composites. The examples show that the method developed in this paper can give consideration to both the reliability demand and the economic aspect of a structure. Since the fuzzy reliability-based optimum design is a ＇soft＇ design, the present results provide a new methodology for the effective evaluation of structural reliability and bring us an alternative optimum design idea.

Sampled-Data Asynchronous Fuzzy Output Feedback Control for Active Suspension Systems in Restricted Frequency Domain

This paper proposes a novel sampled-data asynchronous fuzzy output feedback control approach for active suspension systems in restricted frequency domain.In order to better investigate uncertain suspension dynamics,the sampleddata Takagi-Sugeno(T-S)fuzzy half-car active suspension(HCAS)system is considered,which is further modelled as a continuous system with an input delay.Firstly,considering that the fuzzy system and the fuzzy controller cannot share the identical premises due to the existence of input delay,a reconstructed method is employed to synchronize the time scales of membership functions between the fuzzy controller and the fuzzy system.Secondly,since external disturbances often belong to a restricted frequency range,a finite frequency control criterion is presented for control synthesis to reduce conservatism.Thirdly,given a full information of state variables is hardly available in practical suspension systems,a two-stage method is proposed to calculate the static output feedback control gains.Moreover,an iterative algorithm is proposed to compute the optimum solution.Finally,numerical simulations verify the effectiveness of the proposed controllers.

Multi-Objective Fuzzy Optimum Design Based on Reliability for Offshore Jacket Platforms

In consideration of the fuzzy constraint boundary and through analysis of structural reliability, a model of structural fuzzy optimum design is established based on reliability for offshore jacket platforms. According to the characteristics of offshore jacket platforms, the tolerance coefficient of the constraint boundary is determined with the fuzzy optimization method. The optimum level cut set lambda*, which is the intersection of the fuzzy constraint set and fuzzy objective set, is determined with the bound search method, and then the fuzzy optimum solution to the fuzzy optimization problem is obtained. The central offshore platform SZ36-1 is designed with the fuzzy optimum model based on reliability; the results are compared with those from deterministic optimum design and fuzzy optimum design. The tendency of design variables in the above three methods and its reasons are analyzed. The results of an example show that the fuzzy optimum design based on reliability is stable and reliable.

Predictive Control in Fuzzy Dynamic Environment

This paper investigates the use of fuzzy decision making in predictive control. The use of fuzzy goals and fuzzy constraints in predictive control allows for a more flexible aggregation of the control objectives than the usual weighting sum of squared errors. Compared to the standard quadratic objective function, with the fuzzy decision-making approach, the designer has more freedom in specifying the desired process behavior.

Method for solving fully fuzzy linear programming problems using deviation degree measure

A new fully fuzzy linear programming （FFLP） problem with fuzzy equality constraints is discussed. Using deviation degree measures, the FFLP problem is transformed into a crisp 6-parametric linear programming （LP） problem. Giving the value of deviation degree in each constraint, the 6-fuzzy optimal solution of the FFLP problem can be obtained by solving this LP problem. An algorithm is also proposed to find a balance-fuzzy optimal solution between two goals in conflict： to improve the values of the objective function and to decrease the values of the deviation degrees. A numerical example is solved to illustrate the proposed method.

Time resource management of OAR based on fuzzy logic priority for multiple target tracking

For coping with the multiple target tracking in the presence of complex time-varying environments and unknown target information, a time resource management scheme based on chance-constraint programming（CCP） employing fuzzy logic priority is proposed for opportunistic array radar（OAR）. In this scheme,the total beam illuminating time is minimized by effective time resource allocation so that the desired tracking performance is achieved. Meanwhile, owing to the randomness of radar cross section（RCS）, the CCP is used to balance tracking accuracy and time resource conditioned on the specified confidence level. The adaptive fuzzy logic prioritization, imitating the human decision-making process for ranking radar targets, can realize the full potential of radar. The Bayesian Crame ′r-Rao lower bound（BCRLB） provides us with a low bound of localization estimation root-mean-square error（RMSE）, and equally important, it can be calculated predictively. Consequently, it is employed as an optimization criterion for the time resource allocation scheme. The stochastic simulation is integrated into the genetic algorithm（GA） to compose a hybrid intelligent optimization algorithm to solve the CCP optimization problem. The simulation results show that the time resource is saved strikingly and the radar performance is also improved.

Integrated optimal method for cell formation and layout problems based on hybrid SA algorithm with fuzzy simulation

To adapt to the complex and changeable market environment,the cell formation problems(CFPs) and the cell layout problems(CLPs) with fuzzy demands were optimized simultaneously. Firstly,CFPs and CLPs were described formally. To deal with the uncertainty fuzzy parameters brought,a chance constraint was introduced. A mathematical model was established with an objective function of minimizing intra-cell and inter-cell material handling cost. As the chance constraint of this problem could not be converted into its crisp equivalent,a hybrid simulated annealing(HSA) based on fuzzy simulation was put forward. Finally,simulation experiments were conducted under different confidence levels. Results indicated that the proposed hybrid algorithm was feasible and effective.

A Neuro-Fuzzy Model for QoS Based Selection of Web Service

The automatic selection and composition of Web services rely strongly on the manner to deal with ambiguity inherent to the description of functionalities of these services and the client’s requests. Quality of Service (QoS) criteria become crucial in Web services selection and the problem of checking that a web service satisfies a given level of QOS is considered in recent research works. This paper presents a QoS based automatic classification method of web services. These services give generally similar functionalities and are offered by different providers. The main feature of our Web service selection model is to take advantage of the neuro-fuzzy logic for coping with the imprecision of QoS constraints values.

考虑风光及负荷不确定性的虚拟电厂低碳经济调度

针对风光出力及负荷预测的不确定性对电力系统调度计划产生的影响,提出考虑不确定性的虚拟电厂低碳经济调度方法。首先,以虚拟电厂运行总成本最小为目标,建立优化调度模型;同时考虑到虚拟电厂的碳排放情况,将阶梯型碳交易模型加入目标函数中进行调度;其次,引入模糊机会约束算法,对风光出力及负荷的不确定性进行处理;最后,算例结果表明所提调度模型的有效性,即综合考虑模糊机会约束和阶梯型碳交易的调度模型可有效提高新能源渗透率并降低系统碳排放。在此基础上,可通过设置置信水平来控制风险,保证系统的安全稳定运行。