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Intention prediction is an important link in threat assessment, which has a great impact on the evaluation results. In order to explore the specific role of target intention in threat assessment , a new threat assessment idea is put forward. Firstly, the battlefield situation is analyzed, the threat index system is established and the index is quantified, then the subjective and objective weighting is carried out with the improved analytic network process (ANP) and improved criteria importance though intercrieria correlation (CRITIC), and the traditional threat value is obtained. Finally, the target intention is judged by big data evidence and the threat assessment model is integrated. The results show that after considering the target intention, the threat ranking of the air target remains unchanged, but the threat value gap is larger, so method optimizes the commander to judge the battlefield situation and make more accurate decisions.

The viscosity of ionic liquids (ILs) plays an important role in the chemical industry, material science and environmental science. This work presents a temperature- and pressure-dependent (η-T-P) model based on the norm indices for describing the viscosity of ILs. While the parameters for the temperature and pressure dependence of the viscosity have been generally set as constants in previous work, they are adjusted based on the molecular structures in the η-T-P model. Because ILs consist of only cations and anions, the norm indices are derived from cations and anions, respectively. However, the close connection between the interaction of the cations and anions and IL viscosity cannot be neglected; therefore, another set of norms is further deduced to represent the cation–anion interaction. The η-T-P model is developed using 349 ILs (3228 data points) in the temperature range of 253.15–573.00 K and the pressure range of 0.06–300.00 MPa. Consequently, a η-T-P model is derived with convincing results, as evaluated by the following statistical parameters: the squared correlation coefficient (R2), Fisher significance (F) and the overall average absolute relative deviation (AARD), which are 0.964, 1809 and 4.62%, respectively.

The quantitative structure–activity relationship (QSAR) model is an effective alternative to traditional experimental toxicity testing, which is undoubtedly important for modern environmental risk assessment and property prediction. Based on this background, the toxicological effects of ionic liquids (ILs) against Candida albicans (C. albicans) were studied via the QSAR method. A large diverse group of 141 and 85 ILs that have a minimal inhibitory concentration (MIC) and a minimum fungicidal concentration (MBC) against C. albicans were used to obtain multiple linear regression models. These two models were developed based on matrix norm indexes and proposed based on the atomic character and position. Matrix norm indexes proposed in our research group were used to calculate the toxicity of these ILs towards C. albicans for the first time. These two models precisely estimated the toxicity of these ILs towards C. albicans with a square of correlation coefficient (R2) of = 0.930 and a standard error of estimate (SE) of = 0.254 for pMIC, and for pMBC, R2 = 0.873 and SE = 0.243.

Ionic liquids (ILs) have attracted much attention in the past few years for their distinctive properties. Thermal conductivity plays an important role in industrial applications. This work presents a linear model based on the norm-indexes to describe the relationship between ILs thermal conductivity and their structure as well as temperature and pressure. A total data set of 475 experimental thermal conductivity data points under a wide range of temperatures (273.15–355.07K) and pressures (0.1–20.0 MPa) for five types of ionic liquids containing ammonium, phosphonium, imidazolium, pyridinium, and pyrrolidinium were employed to train and test the model. The results revealed that this proposed method presented a good accuracy with high F of 1540, high R2 of 0.984, and low AARD of 1.45%. In addition, the good results of 5-fold cross-validation, external validation, Y-randomization test, as well as applicability domain further illustrate the stability and reliability of this work. Accordingly, this norm-index...

The hazardous potential of ionic liquids (ILs) is becoming an issue of great concern due to their important role in many industrial fields as green agents. The mathematical model for the toxicological effects of ILs is useful for the risk assessment and design of environmentally benign ILs. The objective of this work is to develop QSAR models to describe the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of ILs against Staphylococcus aureus (S. aureus). A total of 169 and 101 ILs with MICs and MBCs, respectively, are used to obtain multiple linear regression models based on matrix norm indexes. The norm indexes used in this work are proposed by our research group and they are first applied to estimate the antibacterial toxicity of these ILs against S. aureus. These two models precisely and reliably calculated the IL toxicities with a square of correlation coefficient (R2) of 0.919 and a standard error of estimate (SE) of 0.341 (in log unit of mM) for pMIC, and an R2 of 0.913 and SE of 0.282 for pMBC.

The heat capacity of ILs is essential in the chemical engineering and design applications. In this study, the dataset consisting of 5964 heat capacity data points within a wide temperature range (191.13–550.00 K) of 185 ILs was collated. Based on the concept of norm index, a serial of norm indexes were derived and adopted to develop the QSPR model. Here, the temperature parameters were adjusted on the basis of the molecular structure information. The linear model is precise for estimating heat capacity of ILs at variable temperatures with square of correlation coefficient R2 = 0.996, average absolute relative deviation AARD = 2.49% and the root mean square error RMSE = 19.43. Besides, the good results of multiple verification methods further illustrate the stability and reliability of this work. Consequently, this norm-index based work could provide a correlation method to describe the heat capacity of different structures ILs at variable temperatures.