Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO). Most current EMO algorithms perform well on problems with two or three objectives, but encounter difficulties their scalability to many-objective optimization. This paper proposes grid-based algorithm (GrEA) solve problems. Our aim is exploit the potential of approach strengthen selection pressure toward optimal direction while maintaining an extensive uniform distribution among solutions....

It is commonly accepted that Pareto-based evolutionary multiobjective optimization (EMO) algorithms encounter difficulties in dealing with many-objective problems. In these algorithms, the ineffectiveness of Pareto dominance relation for a high-dimensional space leads diversity maintenance mechanisms to play leading role during process, while preference individuals sparse regions results final solutions distributed widely over objective but distant from desired front. Intuitively, there are...

It is challenging to understand the latest trends and summarise state or general opinions about products due big diversity size of social media data, this creates need automated real time opinion extraction mining. Mining online a form sentiment analysis that treated as difficult text classification task. In paper, we explore role pre-processing in analysis, report on experimental results demonstrate with appropriate feature selection representation, accuracies using support vector machines...

In this paper, the robust Hinfin control problem Is considered for a class of networked systems with random communication packet losses. Because limited bandwidth channels, such losses could occur, simultaneously, in channels from sensor to controller and actuator. The loss is assumed obey Bernoulli binary distribution, parameter uncertainties are norm-bounded enter into both system output matrices. presence losses, an observer-based feedback designed robustly exponentially stabilize sense...

In this paper, a synchronization problem is investigated for an array of coupled complex discrete-time networks with the simultaneous presence both discrete and distributed time delays. The addressed which include neural social as special cases are quite general. Rather than commonly used Lipschitz-type function, more general sector-like nonlinear function employed to describe nonlinearities existing in network. infinite delays domain first defined. By utilizing novel Lyapunov-Krasovskii...

In this paper, the robust H/sub /spl infin// filtering problem is studied for stochastic uncertain discrete time-delay systems with missing measurements. The measurements are described by a binary switching sequence satisfying conditional probability distribution. We aim to design filters such that, all possible observations and admissible parameter uncertainties, error system exponentially mean-square stable, prescribed performance constraint met. terms of certain linear matrix inequalities...

In this study, we examine the effects of individual-level culture on adoption and acceptance e-learning tools by students in Lebanon using a theoretical framework based Technology Acceptance Model (TAM). To overcome possible limitations TAM developing countries, extend to include subjective norms (SN) quality work life constructs as additional number cultural variables moderators. The four dimensions masculinity/femininity (MF), individualism/collectivism, power distance uncertainty...

Cloud computing provides promising platforms for executing large applications with enormous computational resources to offer on demand. In a model, users are charged based their usage of and the required quality service (QoS) specifications. Although there many existing workflow scheduling algorithms in traditional distributed or heterogeneous environments, they have difficulties being directly applied environments since differs from by its service-based resource managing method pay-per-use...

Object detection is a well-known task in the field of computer vision, especially small target problem that has aroused great academic attention. In order to improve performance objects, this article, novel enhanced multiscale feature fusion method proposed, namely, atrous spatial pyramid pooling-balanced-feature network (ABFPN). particular, convolution operators with different dilation rates are employed make full use context information, where skip connection applied achieve sufficient...

This technical note is concerned with the sampled-data synchronization control problem for a class of dynamical networks. The sampling period considered here assumed to be time-varying that switches between two different values in random way given probability. addressed first formulated as an exponentially mean-square stabilization new networks involve both multiple probabilistic interval delays (MPIDs) and sector-bounded nonlinearities (SBNs). Then, novel Lyapunov functional constructed...

In this paper, new synchronization and state estimation problems are considered for an array of coupled discrete time-varying stochastic complex networks over a finite horizon. A novel concept bounded H(∞) is proposed to handle the nature networks. Such captures transient behavior network horizon, where degree quantified in terms H(∞)-norm. general sector-like nonlinear function employed describe nonlinearities existing network. By utilizing real-valued Kronecker product, criteria...

It is known that Pareto dominance has its own weaknesses as the selection criterion in evolutionary multiobjective optimization. Algorithms based on (PC) can suffer from problems such slow convergence to optimal front and inferior performance with many objectives. Non-Pareto (NPC), decomposition-based indicator-based criterion, already shown promising results this regard, but high pressure may lead algorithm prefer some specific areas of problem's front, especially when highly irregular. In...

In this technical note, the globally exponential stabilization problem is investigated for a general class of stochastic systems with both Markovian jumping parameters and mixed time-delays. The mode-dependent time-delays consist discrete distributed delays. We aim to design memoryless state feedback controller such that closed-loop system stochastically exponentially stable in mean square sense. First, by introducing new Lyapunov-Krasovskii functional accounts delays, analysis conducted...

In this paper, a novel particle swarm optimization (PSO) algorithm is put forward where sigmoid-function-based weighting strategy developed to adaptively adjust the acceleration coefficients. The newly proposed adaptive takes into account both distances from global best position and its personal position, thereby having distinguishing feature of enhancing convergence rate. Inspired by activation function neural networks, new employed update coefficients using sigmoid function. search...