Accurate classification of encrypted traffic plays an important role in network ***,current methods confronts several problems:inability to characterize traffic that exhibits great dispersion,inability to classify tra...
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Accurate classification of encrypted traffic plays an important role in network ***,current methods confronts several problems:inability to characterize traffic that exhibits great dispersion,inability to classify traffic with multi-level features,and degradation due to limited training traffic *** address these problems,this paper proposes a traffic granularity-based cryptographic traffic classification method,called Granular Classifier(GC).In this paper,a novel Cardinality-based Constrained Fuzzy C-Means(CCFCM)clustering algorithm is proposed to address the problem caused by limited training traffic,considering the ratio of cardinality that must be linked between flows to achieve good traffic ***,an original representation format of traffic is presented based on granular computing,named Traffic Granules(TG),to accurately describe traffic structure by catching the dispersion of different traffic *** granule is a compact set of similar data with a refined boundary by excluding *** on TG,GC is constructed to perform traffic classification based on multi-level *** performance of the GC is evaluated based on real-world encrypted network traffic *** results show that the GC achieves outstanding performance for encrypted traffic classification with limited size of training traffic and keeps accurate classification in dynamic network conditions.
Even though smart meters have been widely used in power systems around the world,many consumers are still finding it hard to participate in demand response(DR)due to flat-rate retail pricing *** address this issue,thi...
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Even though smart meters have been widely used in power systems around the world,many consumers are still finding it hard to participate in demand response(DR)due to flat-rate retail pricing *** address this issue,this paper proposes a coupon-based demand response(CDR)scheme to achieve equivalent dynamic retail prices to inspire consumers’inherent ***,a security-constrained unit commitment optimization model is developed in the day-ahead market to obtain coupon rewards,which are then broadcast to consumers to motivate them to reschedule their power consumption *** evaluate the adjustment value of consumers’power consumption,a collective utility function is proposed to formulate the relationship between power quantity and coupon *** this basis,the security-constrained economic dispatch model is developed in the intra-day market to reschedule generating units’output power according to real-time load demands and fluctuating renewable *** the operation interval,a settlement method is developed to quantify consumers’electricity fees and coupon benefits on a monthly *** proposed CDR scheme avoids real-time iterative bidding process and effectively decreases the difficulty of massive,small consumers participating in *** proposed CDR is implemented in a realistic DR project in China to verify consumers’energy cost and renewables’curtailment can both be decreased.
In this letter, we introduce a novel anti-windup design approach for internal model control (IMC) that addresses the issue of asymmetric input saturation. To enhance closed-loop performance during periods of saturatio...
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This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent *** the multi-agent system dynamics are uncertain,solving regulator equations and the correspond...
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This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent *** the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic Riccati equations is challenging,especially for high-order *** this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent *** is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance ***,the effectiveness of the proposed control method is validated by simulations.
In this paper, a quality diversity optimization method (QDOM) based on an adaptive bound-searching algorithm and diversity-selecting immune algorithm is proposed for solving bilinear matrix inequality (BMI) problems i...
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In medical image analysis, the cost of acquiring high-quality data and annotation by experts is a barrier in many medical applications. Most of the techniques used are based on a supervised learning framework and requ...
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In coastal regions of China,offshore wind farm ex-pansion has spurred extensive research to reduce operational costs in power systems with high penetration of wind ***,frequent extreme weather conditions such as typho...
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In coastal regions of China,offshore wind farm ex-pansion has spurred extensive research to reduce operational costs in power systems with high penetration of wind ***,frequent extreme weather conditions such as typhoons pose substantial challenges to system stability and ***-vious research has intensively examined the steady-state opera-tions arising from typhoon-induced faults,with a limited em-phasis on the transient frequency dynamics inherent to such *** address this challenge,this paper proposes a frequen-cy-constrained unit commitment model that can promote ener-gy utilization and improve *** proposed model ana-lyzes uncertainties stemming from transmission line failures and offshore wind generation through typhoon *** types of power disturbances resulting from typhoon-in-duced wind farm cutoff and grid islanding events are *** addition,new frequency constraints are defined considering the changes in the topology of the power ***,the complex frequency nadir constraints are incorporated into a two-stage stochastic unit commitment model using the piece-wise ***,the proposed model is verified by nu-merical experiments,and the results demonstrate that the pro-posed model can effectively enhance system resilience under ty-phoons and improve frequency dynamic characteristics following fault disturbances.
Riddle-solving requires advanced reasoning skills, pushing Large Language Models (LLMs) to engage in abstract thinking and creative problem-solving, often revealing limitations in their cognitive abilities. In this pa...
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The formulations and approximations of the branch flow model for general(radial and mesh) power networks(General-BranchFlow) are given in this paper. Using different sets of the power flow equations, six formats of th...
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The formulations and approximations of the branch flow model for general(radial and mesh) power networks(General-BranchFlow) are given in this paper. Using different sets of the power flow equations, six formats of the exact General-BranchFlow model are listed. The six formats are mathematically equivalent with each other. Linear approximation and second-order cone programming(SOCP) are then used to derive the six formats of the convex General-BranchFlow model. The branch ampacity constraints considering the shunt conductance and capacitance of the transmission line Π-model are derived. The key foundation of deriving the ampacity constraints is the correct interpretation of the physical meaning of the transmission line Π-model. An exact linear expression of the ampacity constraints of the power loss variable is derived. The applications of the General-BranchFlow model in deriving twelve formats of the exact optimal power flow(OPF) model and twelve formats of the approximate OPF model are formulated and analyzed. Using the Julia programming language, the extensive numerical investigations of all formats of the OPF models show the accuracy and computational efficiency of the General-BranchFlow model. A penalty function based approximation gap reduction method is finally proposed and numerically validated to improve the AC-feasibility of the approximate General-BranchFlow model.
The outputs of renewable energy sources(RESs)are inherently variable and uncertain,such as wind power(WP)and photovoltaic(PV).However,the outputs of various types of RESs in different regions are *** the capacity of R...
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The outputs of renewable energy sources(RESs)are inherently variable and uncertain,such as wind power(WP)and photovoltaic(PV).However,the outputs of various types of RESs in different regions are *** the capacity of RESs could be properly allocated during system planning,variability of the total output could be ***,system reliability and renewable energy(RE)consumption could be *** paper proposes an analytical model for optimal complementary capacity allocation of RESs to decrease variability of the total *** model considers the capacity ratio of RESs as decision variables and the coefficient of variation(CV)of the total output as the objective *** proposed approach transforms the single-level optimization model into a bilevel optimization model and derives an analytical equation that can directly calculate the optimal complementary capacity ratio(OCCR)of system *** studies on wind and solar farms in Xinjiang and Qinghai,China,are performed to verify the effectiveness of the proposed analytical allocation method.
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