Development of self-adaptive back propagation and derivative free training algorithms in artificial neural networks

Three new iterative, dynamically self-adaptive, derivative-free and training parameter free artificial neural network (ANN) training algorithms are developed. They are defined as self-adaptive back propagation, multi-directional and restart ANN training algorithms. The descent direction in self-adaptive back propagation training is determined implicitly by a central difference approximation scheme, which chooses its step size according to the convergence behavior of the error function. This approach trains an ANN when the gradient information of the corresponding error function is not readily available. The self- adaptive variable learning rates per epoch are determined dynamically using a constrained interpolation search. As a result, appropriate descent to the error function is achieved. The multi-directional training algorithm is self-adaptive and derivative free. It orients an initial search vector in a descent location at the early stage of training. Individual learning rates and momentum term for all the ANN weights are determined optimally. The search directions are derived from rectilinear and Euclidean paths, which explore stiff ridges and valleys of the error surface to improve training. The restart training algorithm is derivative free. It redefines a de-generated simplex at a re-scale phase. This multi-parameter training algorithm updates ANN weights simultaneously instead of individually. The descent directions are derived from the centroid of a simplex along a reflection point opposite to the worst vertex. The algorithm is robust and has the ability to improve local search. These ANN training methods are appropriate when there is discontinuity in corresponding ANN error function or the Hessian matrix is ill conditioned or singular. The convergence properties of the algorithms are proved where possible. All the training algorithms successfully train exclusive OR (XOR), parity, character-recognition and forecasting problems. The simulation results with XOR, parity and character recognition problems suggest that all the training algorithms improve significantly over the standard back propagation algorithm in average number of epoch, function evaluations and terminal function values. The multivariate ANN calibration problem as a regression model with small data set is relatively difficult to train. In forecasting problems, an ANN is trained to extrapolate the data in validation period. The extrapolation results are compared with the actual data. The trained ANN performs better than the statistical regression method in mean absolute deviations; mean squared errors and relative percentage error. The restart training algorithm succeeds in training a problem, where other training algorithms face difficulty. It is shown that a seasonal time series problem possesses a Hessian matrix that has a high condition number. Convergence difficulties as well as slow training are therefore not atypical. The research exploits the geometry of the error surface to identify self-adaptive optimized learning rates and momentum terms. Consequently, the algorithms converge with high success rate. These attributes brand the training algorithms as self-adaptive, automatic, parameter free, efficient and easy to use

Virtual teams: A literature review

In the competitive market, virtual teams represent a growing response to the need for fasting time-to-market, low-cost and rapid solutions to complex organizational problems. Virtual teams enable organizations to pool the talents and expertise of employees and non-employees by eliminating time and space barriers. Nowadays, companies are heavily investing in virtual team to enhance their performance and competitiveness. Despite virtual teams growing prevalence, relatively little is known about this new form of team. Hence the study offers an extensive literature review with definitions of virtual teams and a structured analysis of the present body of knowledge of virtual teams. First, we distinguish virtual teams from conventional teams, different types of virtual teams to identify where current knowledge applies. Second, we distinguish what is needed for effective virtual team considering the people, process and technology point of view and underlying characteristics of virtual teams and challenges they entail. Finally, we have identified and extended 12 key factors that need to be considered, and describes a methodology focused on supporting virtual team working, with a new approach that has not been specifically addressed in the existing literature and some guide line for future research extracted

SMEs: ERP or virtual collaboration teams

Small firms are indeed the engines of global economic growth. Small and Medium Enterprises (SMEs) play an important role to promote economic development. SMEs in the beginning of implementing new technologies always face capital shortage and need technological assistance. Available ERP systems do not fulfil the specific requirements of Small firms. SMEs has scarce resources and manpower therefore many SMEs don?t have the possessions to buy and operate an ERP System. On the other hand competition and competitiveness of SMEs have to be strengthened. This paper briefly reviews the existing perspectives on virtual teams and their effect on SMEs management. It also discusses the main characteristics of virtual teams and clarifies the differences aspects of virtual team application in SMEs. After outlining some of the main advantages and pitfall of such teams, it concentrates on comparing of ERP and virtual collaborative teams in SMEs. Finally, it provides evidence for the need of ?Software as a Service (SaaS)? where an application is hosted as a service provided to customers across the web for SMEs as an alternative of ERP. It has been widely argued that ERP disadvantage in SMEs such as administrative expenditure and cost, isolated structure, severe lack of software flexibility, insufficient support of SMEs business and high operating cost, lead SMEs to use virtual collaborative team which is net work base solution

Innovation and R & D activities in virtual team

Innovation plays a central role in economic development, at the regional and national level. In the competitive environment companies are obliged to produce more rapidly, more effectively and more efficiently in new product development, which is a result of research and development (R&D) activities. It is necessary for them to put together different capabilities and services with the goal, through cooperation between suppliers and customers, service providers and scientific institutions to achieve innovations of high quality. Depending on the type of industry, the type of business, the type of innovation and the strategic objectives that have been set, firms will regularly have to modify the way in which their R\&D and innovation are organized. Nowadays, shift from serial to simultaneous and parallel working in innovation has become more commonplace. Literature's have shown that collaboration is as a meta-capability for innovation. By a comprehensive reviewing of literature this article after define virtual teams and its characteristics, addressing virtual environment innovation and the relationship to R&D activities. Finally conclude that innovation cannot be successful, unless the knowledge and information in the R&D project are effectively captured, shared and internalized by the R&D project?s virtual team members

Virtual R&D Teams: A potential growth of education-industry collaboration

Introduction: With the advent of the global economy and high-speed Internet, online collaboration is fast becoming the norm in education and industry 1. Information technology (IT) creates many new inter-relationships among businesses, expands the scope of industries in which a company must compete to achieve the competitive advantage. Information systems and technology allow companies to coordinate their activities in distant geographic locations 2. IT is providing the infrastructure necessary to support the development of new collaboration forms among industry and education. Virtual research and development (R&D) teams represent one such relational form, one that could revolutionize the workplace and provide organizations with unprecedented levels of flexibility and responsiveness 3-4

SMEs; Virtual research and development (R&D) teams and new product development: A literature review

Small and medium-sized enterprises (SMEs) are indeed the engines of global economic growth. Their continued growth is a major subject for the economy and employment of any country. Towards that end, virtual research and development (R&D) could be a viable option to sustain and ease the operations of SMEs. However, literature shows there has not been a great deal of research into the diverse characteristic of virtual R&D teams in SMEs. This article provides a comprehensive literature review on different aspects of virtual R&D teams collected from the reputed publications. The purpose of the literature review is to provide an outline on the structure and dynamics of R&D collaboration in SMEs. Specifying the rationale and relevance of virtual teams, the relationship between virtual R&D team for SMEs and new product development (NPD) has been examined. It concludes with identifying the gaps and feebleness in the existing literature and calls for future research in this area. It is argued to form of virtual R&D team deserves consideration at top level management for venturing into the new product development within SMEs

Modified Stage-Gate: A Conceptual Model of Virtual Product Development Process

In today’s dynamic marketplace, manufacturing companies are under strong pressure to introduce new products for long-term survival with their competitors. Nevertheless, every company cannot cope up progressively or immediately with the market requirements due to knowledge dynamics being experienced in the competitive milieu. Increased competition and reduced product life cycles put force upon companies to develop new products faster. In response to these pressing needs, there should be some new approach compatible in flexible circumstances. This paper presents a solution based on the popular Stage-Gate system, which is closely linked with virtual team approach. Virtual teams can provide a platform to advance the knowledge-base in a company and thus to reduce time-to-market. This article introduces conceptual product development architecture under a virtual team umbrella. The paper describes all the major aspects of new product development (NPD), NPD process and its relationship with virtual teams, Stage-Gate system finally presents a modified Stage-Gate system to cope up with the changing needs. It also provides the guidelines for the successful implementation of virtual teams in new product development

Modified Stage-Gate: A Conceptual Model of Virtual Product Development Process

In today s dynamic marketplace, manufacturing companies are under strong pressure to introduce new products for long-term survival with their competitors. Nevertheless, every company cannot cope up progressively or immediately with the market requirements due to knowledge dynamics being experienced in the competitive milieu. Increased competition and reduced product life cycles put force upon companies to develop new products faster. In response to these pressing needs, there should be some new approach compatible in flexible circumstances. This paper presents a solution based on the popular Stage-Gate system, which is closely linked with virtual team approach. Virtual teams can provide a platform to advance the knowledge-base in a company and thus to reduce time-to-market. This article introduces conceptual product development architecture under a virtual team umbrella. The paper describes all the major aspects of new product development (NPD), NPD process and its relationship with virtual teams, Stage-Gate system finally presents a modified Stage-Gate system to cope up with the changing needs. It also provides the guidelines for the successful implementation of virtual teams in new product development.Comment: 24 page

Critical Factors for New Product Developments in SMEs' Virtual Team

Small and medium enterprises (SMEs) are considered as an engine for economic growth all over the world and especially for developing countries. During the past decade, new product development (NPD) has increasingly been recognized as a critical factor in ensuring the continued survival of SMEs. On the other hand, the rapid rate of market and technological changes has accelerated in the past decade, so this turbulent environment requires new methods and techniques to bring successful new products to the marketplace. Virtual team can be a solution to answer the requested demand. However, literature have shown no significant differences between traditional NPD and virtual NPD in general, whereas NPD in SME’s virtual team has not been systematically investigated in developing countries. This paper aims to bridge this gap by first reviewing the NPD and its relationship with virtuality and then identifies the critical factors of NPD in virtual teams. The statistical method was utilized to perform the required analysis of data from the survey. The results were achieved through factor analysis at the perspective of NPD in some Malaysian and Iranian manufacturing firms (N = 191). The 20 new product development factors were grouped into five higher level constructs. It gives valuable insight and guidelines, which hopefully will help managers of firms in developing countries to consider the main factors in NPD