A Personalized Comprehensive Cloud-Based Method for Heterogeneous MAGDM and Application in COVID-19

This paper proposes a personalized comprehensive cloud-based method for heterogeneous multi-attribute groupdecision-making (MAGDM), in which the evaluations of alternatives on attributes are represented by LTs (linguisticterms), PLTSs (probabilistic linguistic term sets) and LHFSs (linguistic hesitant fuzzy sets). As an eective toolto describe LTs, cloud model is used to quantify the qualitative evaluations. Firstly, the regulation parameters ofentropy and hyper entropy are dened, and they are further incorporated into the transformation process from LTsto clouds for reecting the dierent personalities of decision-makers (DMs). To tackle the evaluation informationin the form of PLTSs and LHFSs, PLTS and LHFS are transformed into comprehensive cloud of PLTS (C-PLTS)and comprehensive cloud of LHFS (C-LHFS), respectively. Moreover, DMs’ weights are calculated based on theregulation parameters of entropy and hyper entropy. Next, we put forward cloud almost stochastic dominance(CASD) relationship and CASD degree to compare clouds. In addition, by considering three perspectives, acomprehensive tri-objective programing model is constructed to determine the attribute weights. Thereby, apersonalized comprehensive cloud-based method is put forward for heterogeneous MAGDM. The validity ofthe proposed method is demonstrated with a site selection example of emergency medical waste disposal inCOVID-19. Finally, sensitivity and comparison analyses are provided to show the eectiveness, stability, exibilityand superiorities of the proposed method.

Globally Exponential Synchronization and Parameter Regulation for Coupled Chaotic System via Adaptive Control

Based on Lyapunov stability theory, an adaptive controller is designed for a class of chaotic systems. Globally exponential synchronization and parameter regulation for couple chaotic systems can be carried out simultaneously. The controller and the regulating law of parameters are directly constructed by analytic formula. Simulation results with some chaotic systems show the effectiveness of the proposed controller.

Regulation Flexibility Assessment and Optimal Aggregation Strategy of Greenhouse Loads in Modern Agricultural Parks

With advances in modern agricultural parks,the rural energy structure has undergone profound change,leading to the emergence of an agricultural energy internet.This integrated system combines agricultural energy utilization,the information internet,and agricultural production.Accordingly,this study proposes a regulation flexibility assessment approach and optimal aggregation strategy of greenhouse loads(GHLs)for modern agricultural parks.First,taking into account the operational characteristics of typical GHLs,refined load demand models for lighting,humidification,and temperature-controlled loads are established.Secondly,the recursive least squares method-based parameter identification method is designed to accurately determine key GHL model parameters.Finally,based on the regulation flexibility of quantitatively evaluated GHLs,GHLs are optimally aggregated into multiple flexible aggregators considering minimal operational cost and greenhouse environmental constraints.The results indicate that the proposed regulation flexibility assessment approach and optimal aggregation strategy of GHLs can alleviate the peak regulation pressure on power grids by flexibly shifting the load demands of GHLs.