Application of particle swarm optimization algorithm in bellow optimum design

In this paper, Particle Swarm Optimization Algorithm （PSOA） is used in problem of the bellow optimum design with constraints, in which the design variables are discrete. To implement bellow optimum design by PSOA, an augmented objective function is constructed based on penalty function and a new updating scheme of penalty parameter s is proposed. A new Discrete PSOA （DPSOA） is proposed. The mathematic model of bellow optimum design is established. Through numerical examples of bellow design, comparing the results of examples by proposed DPSOA with the theory solutions by Net method, it shows that the particle swarm optimization algorithm can be applied to the bellow optimum design successfully and satisfactory results by DPSOA are obtained, which is discrete optimal solution in the feasible domain.     

Coupled particle swarm optimization method with genetic algorithm for the static–dynamic performance of the magneto-electro-elastic nanosystem

As a first attempt, Fourier series expansion (FSE), particle swarm optimization (PSO), and genetic algorithm (GA) methods are coupled for analysis of the static–dynamic performance and propagated waves in the magneto-electro-elastic (MEE) nanoplate. The FSE method is presented for solving the motion equations of the MEE nanoplate. For increasing the performance of genetic algorithms for solving the problem, the particle swarm optimization technique is added as an operator of the GA. Accuracy, convergence, and applicability of the proposed mixed approach are shown in the results section. Also, we prove that for obtaining the convergence results of the PSO and GA, we should consider more than 16 iterations. Finally, it is shown that if designers consider the presented algorithm in their model, the results of phase velocity of the nanosystem will be increased by 27%. A useful suggestion is that there is a region the same as a trapezium in which there are no effects from magnetic and electric potential of the MEE face sheet on the phase velocity of the smart nanoplate, and the region will be bigger by increasing the wavenumber.

     

Multicriteria optimization based on neural network,fuzzy and neuro-fuzzy approximation of decision maker’s utility function

A direct adaptive method of multicriteria optimization based on neural network, fuzzy and neuro-fuzzy approximation of the decision maker’s utility function is introduced. A comparative analysis of efficiency of the various approximation techniques for solving two-and three-criterion optimization test problems is carried out.     

Modeling of a proton exchange membrane fuel cell based on the hybrid particle swarm optimization with Levenberg–Marquardt neural network

This paper presents a nonlinear modeling approach of a proton exchange membrane fuel cell (PEMFC) based on the hybrid particle swarm optimization with Levenberg–Marquardt algorithm neural network (PSO-LM NN). The PSO algorithm converges rapidly during the initial stages of a global search, while it becomes extremely slow around the global optimum. On the contrary, the LM algorithm can achieve faster convergent speed around the global optimum, while it is prone to being trapped in the local minimum. Therefore the hybrid algorithm with a transition from PSO search to LM training is proposed to train the weights and thresholds of neural network, which aims to exploit the advantage of the both algorithms. An accurate mathematical model is an extremely useful tool for the fuel cell design, and neural network is an excellent optional tool for complex nonlinear dynamic system modeling such as PEMFC. In the paper, firstly a highly reduced PEMFC dynamic physical model is established to generate the data for the PSO-LM NN model training and validation, and then the neural network nonlinear autoregressive model based on the PSO-LM algorithm is applied in modeling PEMFC voltage and temperature model, and finally the validation test result demonstrates that the trained PSO-LM NN model can efficiently approach the dynamic behavior of a PEMFC.     

Correction to: Sparse regressions and particle swarm optimization in training high-order Takagi–Sugeno fuzzy systems

Neural Computing and Applications - Unfortunately, the equation 39 has been published incorrectly in the online publication of the article.     

Multicriteria optimization based on neural network approximation of decision maker’s utility function

A direct adaptive method of multicriteria optimization based on neural network approximation of a decision maker’s utility function is introduced. Efficiency of method is analyzed via two- and three- criterion test problems solving. Efficiency testing results are shown. The method implementation as an optimization module for PRADIS (Program for Analysis of Dynamic Systems) is described. Practical application of the method for solving two-criterion optimization problem of combustion engine mechanical subsystem is carried out.     

Evaluating the effect of health warnings in influencing Australian smokers’ psychosocial and quitting behaviours using fuzzy causal network

This paper explores the application of fuzzy causal networks (FCNs) to evaluating effect of health warnings in influencing Australian smokers’ psychosocial and quitting behaviour. The sample data used in this study are selected from the International Tobacco Control Policy Evaluation Survey project. Our research findings have demonstrated that new health warnings implemented in Australia have obvious impacts on smokers’ psychosocial and quitting behaviours. FCN is a useful framework to investigate such impacts that overcome the limitation of using traditional statistical techniques, such as linear regression and logistics regression, to analyse non-linear data.     

On-line kernel clustering based on the general regression neural network and T. Kohonen’s self-organizing map

The clustering system based on the evolving general regression neural network and self-organizing map of T.Kohonen, is proposed in the paper. The tuning of system is based on “lazy” learning and self-learning using the principle “Winner takes more” at the same time as neighborhood function the output signal of the hybrid network is used. The system’ implementation is characterized by numerical simplicity. The evolving neural network processes data in an online mode and doesn’t suffer from the curse of dimensionality.     

Crowdsourcing contests: understanding the effect of competitors’ participation history on their performance

Crowdsourcing contests have become increasingly important and prevalent with the ubiquity of the Internet. Designing efficient crowdsourcing contests is not possible without the deep understanding of the factors affecting individuals’ continuous participation and their performance. Prior studies have mainly focused on identifying the effect of task-specific, environment-specific, organisation-specific, and individual-specific factors on individuals’ performance in crowdsourcing contests. And to our knowledge, there are no or very few studies on evaluating the effect of individuals’ participation history on their performance. This paper aims to address this research gap using a data set from TopCoder. This study derives competitors’ participation history factors, such as participation frequency, participation recency, winning frequency, winning recency, tenure, and last performance to construct models depicting effects of these factors on competitors’ performance in online crowdsourcing contests. The research findings demonstrate that most of competitors’ participation history factors have significant effect on their performance. This paper also indicates that competitors’ participation frequency and winning frequency moderate the relationship between last performance and performance, and relationship between tenure and performance positively. On the other hand, individuals’ participation recency and winning recency moderate relationship between last performance and performance negatively, but have no significant effect on the relationship between tenure and performance.     

Gender differences in the effect of communication on college students’ online decisions

This study focuses on gender differences in the influence of online communication on e-commerce purchase decision strategies. From the literature, we deduce a new theoretical model based on three foundational theories and design a 2 ¹ 2 mixed factorial experiment to test the influence of online communication in cases with and without online communication. This involves analyzing screen-recording data to check the effect of shopping behavior initiation, and using questionnaire research to test differences in the user experience before and after such communication. Finally, we concluded that the influence of online communication differs between men and women, and the influence is largely positive to both males and females.     

Comments on the ‘ fuzzy max ’ operator of Dubois and Prade

The aim of this paper is to study controllability for systems described by first-order evolution equations and for systems described by second-order evolution equations in the case of discrete-time controls. For systems with finite-dimensional controls we present necessary and sufficient conditions for controllability. We show that distributed parameter systems are never finite-step controllable. We also investigate the relations between systems with discrete-time controls and systems with continuous -time controls from the view-point of controllability. Moreover we see the essential difference between the parabolic case and the hyperbolic case.     

Neural network’s selection of color in UI design of social software

Neural Computing and Applications - In recent years, the design of social software UI has become a design research focus in the field of design. Color affects many factors in UI design. However,...     

Dependence of performance indices of a call center on the distribution of calls’ sojourn time in the orbit

The operation of a call center is described in the form of a retrial queuing system. The dependence of its performance indices on the Markovian and two-phase Erlang distributions of calls’ sojourn time in the orbit is considered. An analytical model of an M / M / c / / / E ₂ retrial queuing system is developed. An asymptotic analysis of some characteristics of M / M / c / 0 / 2/ / M and M / M / c / 0 / 2 / / E ₂ systems is performed. An application is developed for solving M / M / c / 0 / N / / N / / E ₂ and M / M / c / 0 / N / / M systems using sparse matrices. Translated from Kibernetika i Sistemnyi Analiz, No. 2, pp. 170–183, March–April 2009.     

On the effect of memory in a quantum prisoner’s dilemma cellular automaton

The disrupting effect of quantum memory on the dynamics of a spatial quantum formulation of the iterated prisoner’s dilemma game with variable entangling is studied. The game is played within a cellular automata framework, i.e., with local and synchronous interactions. The main findings of this work refer to the shrinking effect of memory on the disruption induced by noise.     

The mediating role of the dimensions of the perceived risk in the effect of customers’ awareness on the adoption of Internet banking in Iran

One of the major issues banks are faced with in providing Internet Banking (IB) services is the adoption of these services by the customers. This study seeks answer to the question that whether bank customers’ awareness of the services and advantages of IB is effective in reducing the negative effect of customers’ perceived risk on their intention of IB adoption. To this end, the two constructs of the dimensions of the perceived risk and IB awareness are simultaneously considered. Besides, in the research model, the effect of IB awareness on each dimension of the perceived risk and the effect of these dimensions on intention of IB adoption by the customers are investigated. The results indicate that IB awareness acts as a factor reducing all dimensions of the perceived risk (including time, financial, performance, social, security, and privacy). In addition, it was found out that except for social risk, other dimensions of the perceived risk have significantly negative effect on the intention of IB adoption. Finally, proving the direct and positive effect of IB awareness on adoption intention, it was concluded that the dimensions of customers’ perceived risk plays a mediating role in the positive effect of IB awareness on IB adoption intention. In this respect, management approaches centered on the concept of IB awareness are offered for reducing the dimensions of customers’ perceived risk.     

An inquiry into the applicability of Kantorovich’s idea to the thermodynamic optimization

A feasible region is employed to describe unknown parameters in thermodynamic models. The method is based on interval estimation of experimental observations, and it is applied to thermodynamic optimization of liquid phase in Ag–Mg system. A final feasible region is an overlapping area among all feasible regions calculated from different groups of data. A discussion of computational advantages on this method suggests that it is a promising method for parameter estimation, but its limitations require more studies on problems such as non-linear inequalities, multi-dimensional visualization and uncertainties in experimental conditions.     

Application of DEA in analyzing a bank’s operating performance

This article takes 117 branches of a certain bank in Taiwan in 2006 as the research subject and introduces data envelopment analysis (DEA) to evaluate the operating performances of business units of this bank to provide the reference for a bank’s managers in determining operation strategies. The result indicates that, in overall technical efficiency, the case bank has many inefficient branches distinctly; the average overall technical efficiency of branches is 54.8% and the average pure technical efficiency of branches is 67%, which is probably because of lower loan-to-deposit ratio, leading to excessive input waste. The average scale efficiency of the case bank during the sample period is 82%. The ratio of resource waste due to technical inefficiency is 45.2%, of which 55.03% is due to pure technical inefficiency.     

ICT: performance evaluation of community development worker’s in South Africa on e-skills*

ABSTRACT

Community development service practitioners have been increasingly burdened with a broader range of responsibilities and ICT could enhance their productivity. Therefore, it is prudent to incorporate information communication technology (ICT) skills into the skills matrix required by the practitioners in order to deliver the service effectively. Furthermore, ICT use is prevalent in almost every organization, therefore, ICT can also serve as a major factor in flexibility of delivery of community development service to the communities, but only if the practitioners possess adequate skills in using ICT tools (software applications) in retrieving, presenting and disseminating valuable and adequate information within the workplace to the parties involved. The study determines the current work conditions, level of performance and expertise in the use of ICT among community development workers (CDWs) in KwaZulu-Natal, South Africa, by evaluating their abilities and experiences, with a view to identify the areas to enhance their effectiveness. Determining the competency of their use of ICT applications is not an easy task; thus a survey methodology was adopted, with a sample of 189 CDWs (63% female and 37% male). Respondents were given the opportunity to rate of their own current ability to use common computer software applications.     

Note on the Structure of Kruskal’s Algorithm

We study the merging process when Kruskal’s algorithm is run with random graphs as inputs. Our aim is to analyze this process when the underlying graph is the complete graph on n vertices lying in [0,1] ^d , and edge set weighted with the Euclidean distance. The height of the binary tree explaining the merging process is proved to be Θ(n) on average. On the way to the proof, we obtain similar results for the complete graph and the d-dimensional square lattice with i.i.d. edge weights.     

Perspectives on management theory’s application in the internet of things research

Information Systems and e-Business Management - The growing use of the internet of things (IoT) has provided businesses with a new opportunity. This study performed a systematic literature review...