A new initial population strategy has been developed to improve the genetic algorithm for solving well-known combinatorial optimization problem, traveling salesman problem. Based on k -means algorithm, we propose a restructure route by reconnecting each cluster. The clusters, which randomly disconnect link connect its neighbors, have ranked in advance according distance among cluster centers, so that can be composed of random routes. This process is<mml:math...

Evolutionary multitask optimization (EMTO) is a newly emerging research area in the field of evolutionary computation. It investigates how to solve multiple problems (tasks) at same time via algorithms (EAs) improve on performance solving each task independently, assuming if some component tasks are related then useful knowledge (e.g., promising candidate solutions) acquired during process one may assist (and also benefit from) other tasks. In EMTO, relatedness typically unknown advance and...

Dempster–Shafer evidence theory is widely used in information fusion. However, it may lead to an unreasonable result when dealing with high conflict evidence. In order solve this problem, we put forward a new method based on the credibility of First, novel belief entropy, Deng applied measure volume and then discounting coefficients each are obtained. Finally, weighted averaging system, Dempster combination rule was realize A role presented for multi-sensor data fusion fault diagnosis. It...

Abstract Smart windows regulate the indoor solar radiation by adjusting their optical transmissive properties, offering an efficient way toward energy‐saving buildings, vehicles, etc. Electrochromism is one of most promising solutions due to its simple control, versatile colors. Yet, electrochromics cannot give zero‐transmission through whole visible range, leading that can always be looked and limited for applications in public sector. In this work, poly( N ‐isopropylacrylamide) (PNIPAm)...

In real applications, how to measure the uncertain degree of sensor reports before applying data fusion is a big challenge. this paper, in frame Dempster-Shafer evidence theory, weighted belief entropy based on Deng proposed quantify uncertainty information. The weight relative scale proposition with regard discernment (FOD). Compared some other measures framework, new focuses information represented by not only mass function, but also FOD, which means less loss processing. After that,...

Dempster–Shafer evidence theory is widely used in modeling and reasoning uncertain information real applications. Recently, a new perspective of with the negation was proposed has attracted lot attention. Both basic probability assignment (BPA) BPA framework can model reason information. However, how to address uncertainty modeled as still an open issue. Inspired by measures theory, method measuring proposed. The belief entropy named Deng entropy, which attention among researchers, adopted...

Abstract Failure mode and effects analysis (FMEA) is an important risk tool that has been widely used in diverse areas to manage factors. However, how the uncertainty FMEA assessments still open issue. In this paper, a novel model based on improved pignistic probability transformation function Dempster–Shafer evidence theory (DST) grey relational projection method (GRPM) proposed improve accuracy reliability with FMEA. The basic assignment (BPA) DST of experts respect each factor. Dempster’s...

Failure mode and effects analysis is an important methodology, which has been extensively used to evaluate the potential failures, errors, or risks in a system, design, process. The traditional method utilizes risk priority number ranking system. This determines by multiplying failure factor values. Dempster–Shafer evidence theory combined with due its effectiveness dealing uncertain subjective information. However, since evaluation of different experts may be some even conflict each other,...

With the development of unmanned aerial vehicle (UAV) and artificial intelligence (AI) technology, Intelligent UAV will be widely used in future autonomous combat. Previous researches on combat within visual range (WVR) have limitations due to simplifying assumptions, limited robustness, ignoring sensor errors. In this paper, order consider error aircraft sensors, we model WVR as a state-adversarial Markov decision process (SA-MDP), which introduce small adversarial perturbations state...

Dempster-Shafer evidence theory (D-S theory) has been widely used in many information fusion systems since it was proposed by Dempster and extended Shafer. However, how to determine the basic probability assignment (BPA), which is main first step D-S theory, still an open issue, especially when given environment world, means frame of discernment incomplete. In this paper, a method generalized world proposed. Frame established first, then triangular fuzzy number models identify target are...

Distributed multi-agent collaborative decision-making technology is the key to general artificial intelligence. This paper takes self-developed Unity3D combat environment as test scenario, setting a task that requires heterogeneous unmanned aerial vehicles (UAVs) perform distributed and complete cooperation task. Aiming at problem of traditional proximal policy optimization (PPO) algorithm’s poor performance in field complex collaboration scenarios based on training framework Ray, Critic...

Supplier selection is a significant issue of multicriteria decision-making (MCDM), which has been heavily studied with classical fuzzy methodologies, but the reliability knowledge from domain experts not efficiently taken into consideration.<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>Z</mml:mi></mml:mrow></mml:math>-number introduced by Zadeh more power to describe human being uncertain information considering both restraint and reliability. In this...

In this paper, we devise beampattern synthesis algorithms for sparse arrays using the alternating direction method of multipliers (ADMM). Unlike usual weighted l1 norm, utilize lp norm array weight vector, where 0 <; p 1, as objective function to enhance its sparsity arbitrary configurations. To solve resultant nonconvex and nonlinear optimization problem, introduce auxiliary variables decouple vector in from complicated constraints on main lobes sidelobes, then, are updated alternately via...

This letter addresses the problem of phase-only antenna beampattern synthesis. With given magnitudes weight vector, we introduce a scaling factor to accurately represent shape constraints on both mainlobe and sidelobe regions. Moreover, derive an iterative optimization method solve resultant efficiently. The performance proposed is demonstrated via numerical examples.

How to quantify the uncertain information in framework of Dempster-Shafer evidence theory is still an open issue. Quite a few uncertainty measures have been proposed framework, however, existing studies mainly focus on mass function itself, available represented by scale frame discernment (FOD) body ignored. Without taking full advantage evidence, methods are somehow not that efficient. In this paper, modified belief entropy considering FOD and relative focal element with respect FOD....

Deep neural networks have evolved significantly in the past decades and are now able to achieve better progression of sensor data. Nonetheless, most deep models verify ruling maxim learning—bigger is better—so they very complex structures. As become more complex, computational complexity resource consumption these increasing significantly, making them difficult perform on resource-limited platforms, such as platforms. In this paper, we observe that different layers often pruning...