Dynamic interval multiobjective optimization problems (DI-MOPs) are very common in real-world applications. However, there few evolutionary algorithms (EAs) that suitable for tackling DI-MOPs up to date. A framework of dynamic cooperative co-evolutionary based on the similarity is presented this paper handle DI-MOPs. In framework, a strategy decomposing decision variables first proposed, through which all divided into two groups according between each variable and parameters. Following that,...

Abstract As high amounts of new energy and electric vehicle (EV) charging stations are connected to the distribution network, voltage deviations likely occur, which will further affect power quality. It is challenging manage quality control a network only relying on traditional reactive mode. If regulation potentials EVs can be tapped, it greatly reduce optimization pressure network. Keeping this in mind, our reasearch first adds model with forms energy, then multi-objective model, achieving...

Dynamic multi-objective optimization problems (DMOPs) not only involve multiple conflicting objectives, but these objectives may also vary with time, raising a challenge for researchers to solve them. This paper presents cooperative co-evolutionary strategy based on environment sensitivities solving DMOPs. In this strategy, new method that groups decision variables is first proposed, in which all the are partitioned into two subcomponents according their interrelation environment. Adopting...

To balance the unexpected power disturbances, an independent system operator (ISO) should assign dynamic regulation commands to all resources via automatic generation control (AGC) dispatch. It can be described as a bi-objective Pareto optimization by considering minimizations of total deviation and mileage payment. In this work, novel dropout deep neural network assisted transfer learning (DDNN-TL) is proposed rapidly approximate high-quality optimal solutions for AGC Firstly, training data...

As the length of electrocardiogram (ECG) sequences increases, most current transformer models demand substantial computational resources for ECG arrhythmia detection. Additionally, conventional single-scale tokens encounter difficulties in accommodating various patterns arrhythmia. Thus, this study, a refined-attention model detection was proposed. Our introduces two refined attention mechanisms, namely, diag- and gated linear attentions, effectively alleviating burdens associated with...

In this paper, a hybrid compact-CIP scheme is proposed to solve Korteweg-de Vries-Burgers equation.The nonlinear advective terms are computed based on the classical constrained interpolation profile (CIP) method, which coupled with high-order compact for third-order derivatives in strong stability preserving Runge-Kutta time discretizations adopted work.A test case presented demonstrate high-resolution properties of scheme.

By introducing two pairs of conjugate exponents and estimating the weight coefficients, we establish reverse versions Hilbert-type inequalities, as described by Jin (J. Math. Anal. Appl. 340:932-942, 2008), prove that constant factors are best possible. As applications, some particular results considered.

Large-scale renewable energy sources connected to the grid bring new problems and challenges automatic generation control (AGC) of power system. In order improve dynamic response performance AGC, a biobjective complementary (BOCC) with high-participation storage resources (ESRs) is established, minimization total deviation regulation mileage payment. To address this problem, strength Pareto evolutionary algorithm employed quickly acquire high-quality front for BOCC. Based on entropy weight...

This study addresses dynamic task allocation challenges in coordinated surveillance involving multiple unmanned aerial vehicles (UAVs). A significant concern is the increased UAV flight distance resulting from assignment of new missions, leading to decreased reconnaissance efficiency. To tackle this issue, we introduce a collaborative multi-target and multi-UAV scheme. Initially, multitasking constrained multi-objective optimization framework (MTCOM) employed optimize time static scenarios....

AbstractAbstractBased on the general non-information prior distribution, we study Bayes estimations of parameter Exponential-Poisson Distribution under some symmetrical and unsymmetrical loss functions. As b is fixed, Bayesian another l are given. Simulation studies performed to access accuracy different estimations. The simulation result illustrates random sample size could select functions, then, it improved precision unknown parameters functions.Keywords: distributionGeneral priorLoss...

The dynamic multi-objective optimization problems (DMOPs) have brought great challenges to the traditional evolutionary algorithms because of their constantly changing Pareto set(PS) and front(PF). In order track change PS PF quickly keep diversity population, prediction-based methods shown prospects. However, most current utilize linear models predict PS. When between different environments has nonlinear relationship, this kind method can not accurately at a new environment. paper,...

This paper investigates the low-priority customers' strategic behavior in single-server queueing system with general service time and two customer types. The priority is preemptive resume, which means that if a high-priority enters are serving customer, arriving preempts facility preempted returns to head of queue for his own class. who resumes at point interruption upon reentering system. customer's dilemma whether join or balk based on linear reward-cost structure. Two cases distinguished...

Aiming at the shortcomings of existing control law based on global information, this article studies coverage problem a given region in plane using team USVs. The goal, which is to cover search domain multiple mobile sensors so that each point surveyed until certain preset level achieved, formulated mathematically precise statement. adaptive presented enables multi-USV navigate complex environment presence unknown obstacles and guarantees fully connected system attains goal. In particular,...