Reasonable allocation of carbon emission rights aids in the realization goal reduction. The purpose this paper is to examine how power sector Yangtze River Economic Belt (the YREB) are distributed. YREB spans China’s eastern, central, and western areas. levels development resource endowment differ significantly across regions, resulting great heterogeneity provinces’ distribution sector. ZSG–DE...

In order to achieve its 2030 carbon emission peak target, China needs adjust and allocate energy consumption initial allowances for each province in a phased planned manner. Thus, this study applied an improved dynamic undesirable zero-sum-gains slacks-based-measure (ZSG-SBM) model evaluate provincial CO2 reduction scenarios allocation 2015–2019 calculate the optimal values of 2030. The results...

data envelopment analysis (dea) models with interval inputs and outputs have been rarely discussed in dea literature. this paper, using the enhanced russell measurement proposes an extended model which permits the presence of interval scale variables which can take both negative and positive values. the model is compared with most well-known dea models of which include the ccr model, the bcc mo...

An original data envelopment analysis (DEA) model is to evaluate each decision-making unit (DMU) with a set of most favorable weights of performance indices. The efficient DMUs obtained from the original DEA construct an efficient (bestpractice) frontier. The original DEA can be considered to identify good (efficient) performers in the most favorable scenario. For the purpose of identifying bad...

This paper processes a unification of Fuzzy TOPSIS and Data Envelopment Analysis DEA to select the units with most efficiency. This research is a two-stage model designed to fully rank the organizational alternatives, where each alternative has multiple inputs and outputs. First, the alternative evaluation problem is formulated byData Envelopment Analysis DEA and separately formulates each pair...

The study of zero-shot generalisation (ZSG) in deep Reinforcement Learning (RL) aims to produce RL algorithms whose policies generalise well novel unseen situations at deployment time, avoiding overfitting their training environments. Tackling this is vital if we are deploy reinforcement learning real world scenarios, where the environment will be diverse, dynamic and unpredictable. This survey...

Amiodarone (AMD)-induced pulmonary toxicity (AIPT) is the most life-threatening side-effect of AMD treatment. N-Monodesethylamiodarone (DEA), an active metabolite of AMD, also exhibits cytotoxicity and tends to accumulate in the lung more intensively than AMD. In this study, we characterized the mechanism of DEA accumulation using A549 cells as a model of the alveolar epithelium. Typical ATP-de...

Risk early-warning of natural disasters is a very intricate non-deterministic prediction, and it was difficult to resolve the conflicts and incompatibility of the risk structure. Risk early-warning factors of natural disasters were differentiated into essential attributes and external characters, and its workflow mode was established on risk early-warning structure with integrated Entropy and D...

Traditional DEA models deal with measurements of relative efficiency of DMUs regarding multiple-inputs vs. multiple-outputs. One of the drawbacks of these models is the neglect of intermediate products or linking activities. After pointing out needs for inclusion of them in DEA models, we propose a slacks-based network DEA model that can deal with intermediate products. Using this model we can ...

in data envelopment analyze (dea) the scale efficiency in the input-oriented ccr model is less than or equal to the scale efficiency in dea based on the fractional analysis (dea-r). also, the scale efficiency in case of multiple inputs and one output and vice versa the scale efficiencies are equal in dea and dea-r. in this paper, first, dea-r model with weight restrictions when there is relativ...