An adaptive dwell time scheduling model for phased array radar based on three-way decision

Real-time resource allocation is crucial for phased array radars to undertake multi-task with limited resources such as in the situation of multi-target tracking, in which targets need to be prioritized so that resources can be allocated accordingly and effectively. In this paper, a three-way decision-based model is proposed for adaptive scheduling of phased radar dwell time. Using the model, the threat posed by a target is measured by an evaluation function, and therefore, a target is assigned to one of the three possible decision regions, i.e., positive region, negative region, and boundary region. A different region has a various priority in terms of resource demand, and as such, a different radar resource allocation decision is applied to each region to satisfy different tracking accuracy of multi-target. In addition, the dwell time scheduling model can be further optimized by implementing a strategy for determining a proper threshold of three-way decision making to optimize the thresholds adaptively in real-time. The advantages and the performance of the proposed model has been verified by experimental simulations with comparison to the traditional two-way decision model and the three-way decision model without threshold optimization. The experiential results have demonstrated that the performance of the proposed model has a certain advantage in detecting high threat targets. 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works

Threat assessment of aerial targets based on improved GRA-TOPSIS method and three-way decisions

Target threat assessment is a critical aspect of information warfare and can offer valuable auxiliary support to combat command decision-making. Aiming to address the shortcomings of three decision-making methods in air combat target assessment, such as the inability to effectively handle uncertain situation information and quantitatively rank the decision-making targets according to their importance, a dynamic intuitionistic fuzzy decision model based on the improved GRA-TOPSIS method and three-way decisions is proposed. First, the target attribute weight is obtained by cosine intuitionistic fuzzy entropy algorithm; then, a novel intuitionistic fuzzy distance measure is introduced, and grey incidence analysis and TOPSIS are used to build the conditional probability for three-way decisions that fully utilize the existing information and reflect the consistency of dynamic change trend; finally, the comprehensive loss function matrix is constructed and the threat classification results are obtained using the decision rules. The example analysis shows that the proposed method can not only effectively handle complex battlefield situations and dynamic uncertain information, but it can also classify targets, improving the effectiveness and rationality of decision-making and providing a reference basis for scientific command decision-making

On improved RCM model to theart evaluation for radiation sesource

Focusing on the deficiency of intuition, real-time and complexity of threat evaluation of radiation resource, an algorithm based on improved radar chart method (RCM) is proposed in this paper. In the algorithm proposed, coarse sorting is integrated with fine sorting to obtain a more accurate and reliable result of threat evaluation. Coarse sorting is applied to sequence all the radiation resource roughly according to radar operation mode, and reduce the task priority of low-threat radiation resource. Then, on the basis of improved RCM, fine sorting is applied to sequence the radiation resource with same radar operation mode. Finally, obtain the results of threat evaluation which combined coarse sorting with fine sorting. Simulation analysis shows the correctness and effectiveness of this algorithm. Comparing with classical method of threat evaluation of radiation resource based on RCM, the algorithm proposed in this paper is more visual in image and can work quickly with lower complexity

AHP-TOPSIS integration extended with Pythagorean fuzzy sets for information security risk analysis

Risk analysis (RA) contains several methodologies that object to ensure the protection and safety of occupational stakeholders. Multi attribute decision-making (MADM) is one of the most important RA methodologies that is applied to several areas from manufacturing to information technology. With the widespread use of computer networks and the Internet, information security has become very important. Information security is vital as institutions are mostly dependent on information, technology, and systems. This requires a comprehensive and effective implementation of information security RA. Analytic hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are commonly used MADM methods and recently used for RA. In this study, a new RA methodology is proposed based on AHP-TOPSIS integration extended with Pythagorean fuzzy sets. AHP strengthened by interval-valued Pythagorean fuzzy numbers is used to weigh risk parameters with expert judgment. Then, TOPSIS with Pythagorean fuzzy numbers is used to prioritize previously identified risks. A comparison of the proposed approach with three approaches (classical RA method, Pythagorean fuzzy VIKOR and Pythagorean fuzzy MOORA) is also provided. To illustrate the feasibility and practicality of the proposed approach, a case study for information security RA in corrugated cardboard sector is executed.No sponso

Mixed-attitude three-way decision model for aerial targets: Threat assessment based on IF-VIKOR-GRA method

Assessing potential threats typically necessitates the use of a robust mathematical model, a comprehensive evaluation method and universal decision rules. A novel approach is utilized in this study to optimize existing threat assessment (TA) algorithms and three-way decision models (3WDMs) are leveraged that incorporate decision-theoretic rough sets (DTRSs) within dynamic intuitionistic fuzzy (IF) environments to create a mixed-attitude 3WDM based on the IF-VIKOR-GRA method in the context of aviation warfare. The primary objectives of this study include determining conditional probabilities for IF three-way decisions (3WDs) and establishing mixed-attitude decision thresholds. Both the target attribute and loss function are expressed in the form of intuitionistic fuzzy numbers (IFNs). To calculate these conditional probabilities, an IF technique is used to combine the multi-attribute decision-making (MADM) method VIKOR and the grey relational analysis (GRA) method, while also taking into account the risk-related preferences of decision-makers (DMs). Optimistic and pessimistic 3WDMs are developed from the perspectives of membership degree and non-membership degree, then subsequently integrated into the comprehensive mixed-attitude 3WDM. The feasibility and effectiveness of this methodology are demonstrated through a numerical example and by comparison to other existing approaches

The effectiveness of IF-MADM (intuitionistic-fuzzy multi-attribute decision-making) for group decisions: methods and an empirical assessment for the selection of a senior centre

This study determines the effectiveness of intuitionistic-fuzzy multi-attribute decision-making (IF-MADM) for making group decisions in practice. The effectiveness of the method is measured in terms of four dimensions: applicability, efficacy, efficiency and informativeness. To measure the efficacy, an IF-MADM model that has been recently proposed, AHP and the TOPSIS approach, which are compensatory models for group MADM, are used to model and solve the same collective decision. Using non-parametric statistical tests for data analytics, a ‘similarity confirmation method’ is proposed for a pair-wise test. This is to determine whether the score vectors are similar. Score vectors are used to determine the final ordinal ranks and whose scales differ greatly for different MADM methods. Since the latter two MADM models are both trustworthy with a known range of applications, any similarity in the results verifies the efficacy of IF-MADM. Using this process, the applicability of IF-MADM modelling is demonstrated. The efficiency and informativeness are also benchmarked and justified in terms of the model’s ability to produce a more informed decision. These results are of interest to practitioners for the selection and application of MADM models. Finally, the selection of a senior centre, which is a real group decision problem, is used to illustrate these. This extends the empirical application of IF-MADM, as relatively few studies practically compare issues for IF-MADM with those for other MADM models. The study also supports a rarely studied non-clinical healthcare decision that is relevant because there are many aging societies

Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches