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The purpose of this paper is to propose an extensiveness intelligent hybrid model to short-term load electricity forecast that can simultaneously model the seasonal complicated nonlinear uncertain patterns in the data. For this purpose, a fuzzy seasonal version of the multilayer perceptrons (MLP) is developed.

In this paper, an extended fuzzy seasonal version of classic MLP is proposed using basic concepts of seasonal modeling and fuzzy logic. The fundamental goal behind the proposed model is to improve the modeling comprehensiveness of traditional MLP in such a way that they can simultaneously model seasonal and fuzzy patterns and structures, in addition to the regular nonseasonal and crisp patterns and structures.

Eventually, the effectiveness and predictive capability of the proposed model are examined and compared with its components and some other models. Empirical results of the electricity load forecasting indicate that the proposed model can achieve more accurate and also lower risk rather than classic MLP and some other fuzzy/nonfuzzy, seasonal nonseasonal, statistical/intelligent models.

One of the most appropriate modeling tools and widely used techniques for electricity load forecasting is artificial neural networks (ANNs). The popularity of such models comes from their unique advantages such as nonlinearity, universally, generality, self-adaptively and so on. However, despite all benefits of these methods, owing to the specific features of electricity markets and also simultaneously existing different patterns and structures in the electrical data sets, they are insufficient to achieve decided forecasts, lonely. The major weaknesses of ANNs for achieving more accurate, low-risk results are seasonality and uncertainty. In this paper, the ability of the modeling seasonal and uncertain patterns has been added to other unique capabilities of traditional MLP in complex nonlinear patterns modeling.

The purpose of this paper is to propose a new linear-nonlinear data preprocessing-based hybrid model to achieve a more accurate result at a lower cost for wind power forecasting. For this purpose, a decomposed based series-parallel hybrid model (PKF-ARIMA-FMLP) is proposed which can model linear/nonlinear and certain/uncertain patterns in underlying data simultaneously.

To design the proposed model at first, underlying data are divided into two categories of linear and nonlinear patterns by the proposed Kalman filter (PKF) technique. Then, the linear patterns are modeled by the linear-fuzzy nonlinear series (LLFN) hybrid models to detect linearity/nonlinearity and certainty/uncertainty in underlying data simultaneously. This step is also repeated for nonlinear decomposed patterns. Therefore, the nonlinear patterns are modeled by the linear-fuzzy nonlinear series (NLFN) hybrid models. Finally, the weight of each component (e.g. KF, LLFN and NLFN) is calculated by the least square algorithm, and then the results are combined in a parallel structure. Then the linear and nonlinear patterns are modeled with the lowest cost and the highest accuracy.

The effectiveness and predictive capability of the proposed model are examined and compared with its components, based models, single models, series component combination based hybrid models, parallel component combination based hybrid models and decomposed-based single model. Numerical results show that the proposed linear-nonlinear data preprocessing-based hybrid models have been able to improve the performance of single, hybrid and single decomposed based prediction methods by approximately 66.29%, 52.10% and 38.13% for predicting wind power time series in the test data, respectively.

The combination of single linear and nonlinear models has expanded due to the theory of the existence of linear and nonlinear patterns simultaneously in real-world data. The main idea of the linear and nonlinear hybridization method is to combine the benefits of these models to identify the linear and nonlinear patterns in the data in series, parallel or series-parallel based models by reducing the limitations of the single model that leads to higher accuracy, more comprehensiveness and less risky predictions. Although the literature shows that the combination of linear and nonlinear models can improve the prediction results by detecting most of the linear and nonlinear patterns in underlying data, the investigation of linear and nonlinear patterns before entering linear and nonlinear models can improve the performance, which in no paper this separation of patterns into two classes of linear and nonlinear is considered. So by this new data preprocessing based method, the modeling error can be reduced and higher accuracy can be achieved at a lower cost.

The purpose of this paper is to improve the capability of managers to forecast revenues and develop marketing plans for B2B component products.

The methodology used is a dynamic market simulation at the product level. A previously developed consumer goods speciality product forecasting model is extensively modified to capture the different parameters (i.e. direct selling) relevant to a business‐to‐business (B2B) component goods product category. A dynamic simulation is developed using a set of equations developed to capture the marketing mix. Using just the demand equation (total supply exogenous) and employing the entire model (supply endogenous), sales are predicted.

The key findings are that the simulation produced more accurate (lower error) forecasts. The dynamic simulation for total demand for B2B auto components produced a mean absolute percentage error (MAPE) of 8.5 percent, comparing favorably with the average MAPEs of 30 percent achieved by 168 companies forecasting B2B products.

The main research limitation is that the model is limited to B2B component products.

The practical implication of the model is that it improves the ability of marketing managers to successfully reach revenue targets.

This improved ability adds value to the B2B component marketing manager's planning process by providing a method of specifying a marketing plan that is likely to result in revenue that achieves or exceeds the target revenue and knowledge of what marketing mix levels would move present sales to meet or exceed target.

Considering the importance and the broad applications of the Fourth Industrial Revolution in various organizations and industries and enjoying the many benefits of this digital transformation framework, organizations need to measure their Industry 4.0 readiness as a starting point and take steps to achieve the strategic goals of Industry 4.0. This study aims to design a comprehensive and practical model that can determine Industry 4.0 readiness level, allowing organizations to implement and exploit technological constituents of this phenomenon.

A systematic literature review (SLR) methodology was used to evaluate and summarize a clear and comprehensive literature overview of Industry 4.0 readiness models and to certify the validity and transparency of the review process. After reviewing 71 articles and survey and then the consensus of Industry 4.0 experts, the 10 dimensions of the 4.0 Industry readiness model were finalized with their indicators having the most frequency in the published articles and models.

The application of the SLR to the development of the new Industry 4.0 readiness model which includes 10 dimensions and 37 indicators and can assess the Industry 4.0 readiness of firms and industries accurately and effectively.

An extensive review of the previous literature yielded the current Industry 4.0 readiness model. The comprehensiveness of this model leads to its wide application in different companies. Future research suggestions are presented at the end of the manuscript.

The concept of the Fourth Industrial Revolution and the application of its technologies are vague and complicated for many organizations and managers, while the need to implement the components and technologies of Industry 4.0 is essential to achieve organizational goals. The presented readiness model helps companies to measure their readiness to enter the Fourth Industrial Revolution and achieve long-term goals.

In this study, an attempt was made to examine the Industry 4.0 readiness models thoroughly and extensively and identify their different approaches. Finally, a comprehensive and multi-dimensional readiness model is presented to assess the position of organizations in order to enter Industry 4.0.

The purpose of this paper is to attempt to integrate manufacturing system analysis to obtain system‐wide optimized solutions and to increase the level of comprehensiveness of the manufacturing system modelling and to develop method of characterization of manufacturing systems based on its structure.

Elements constituting the manufacturing plant and the interactions between them have been identified through a literature survey and have been represented by graph‐based model. The matrix models and the variable permanent function models are developed for carrying out decomposition, characterization and the total analysis.

Structural patterns and combination sets of subsystems interacting in various ways have been recognized as capabilities of manufacturing system in different performance dimensions. The permanent function of the manufacturing system matrix has been proposed as a systematic technique for structural analysis of manufacturing system. Also, the terms of permanent multinomial characterize the manufacturing systems uniquely and are highly useful for computational storage, retrieval, communication as well as analysis of the structural information of manufacturing system.

The structure‐based characterization technique developed has the potential of aiding the ongoing research activities in the field of benchmarking, and business process reengineering. The graph theory‐based methodology will serve as a framework to develop composite performance measures building on the performance measures of the individual elements of the manufacturing system graph in various dimensions.

Through the use of proposed methodology, a manufacturing manager will be able to make better informed decisions towards organizational efforts of improving the productivity and speed. For aiding several decisions, different “what‐if” scenarios may be generated with several structural modifications.

This graph theory‐based methodology is a novel mechanism to seamlessly integrate manufacturing system giving way to system wide optimization. The paper is an attempt to address the need for comprehensive and integrated analysis of the manufacturing system.

Business model (BM) canvases have been used in educational institutions and business incubators for over a decade to assist students and start-up entrepreneurs in developing their business projects. Given the urgency of tackling sustainability challenges, several tools have emerged to stimulate sustainable business modeling (SBM). However, these tools are often too complex for nonexperts in business modeling or sustainability, and thus insufficiently user-friendly for educational contexts. This study aims to address this pedagogical gap by describing the design process of the responsible business model canvas (RBMC).

The authors relied on a design science research methodology involving the active participation of end users, entrepreneurship educators, business coaches and external partners. The authors proposed four criteria and ten subcriteria to analyze existing SBM canvases based on their user-friendliness and to design the initial prototype of the RBMC. The RBMC was subsequently tested in various settings, including classroom assignments and business incubation programs, with over 1,000 university students. The tool was refined and assessed throughout the development process, incorporating feedback from focus groups with start-up entrepreneurs.

Through the development process, the authors created a user-friendly tool to help novice student and start-up entrepreneurs integrate sustainability into their BMs: the RBMC. The canvas consists of 14 building blocks grouped into four areas: consistency (mission, vision, values), desirability (value propositions, customer segments, users and beneficiaries, customer relationships and channels), feasibility (key activities, key resources, key partners and stakeholders and governance) and viability (cost structure, revenues streams, negative impacts and positive impacts).

The research methods and user-friendliness criteria in this study can be applied in other contexts to design tools to support sustainable entrepreneurship education. While the RBMC is currently being used in several educational institutions throughout the world, its impacts in different pedagogical and cultural settings require further validation.

The RBMC is a user-friendly tool to introduce students and start-up entrepreneurs to SBM. It helps raise users’ awareness about sustainability concerns, challenging them to consider issues they might have otherwise overlooked. Some participants even shifted their outlook and were motivated to develop a long-term vision integrating compensatory, mitigative or corrective actions into their BMs.

The RBMC is the outcome of a balanced approach that combines both pragmatic (i.e. user-friendliness) and normative (i.e. sustainability) perspectives. It provides users with a systematic approach for integrating and applying sustainability issues in their business projects.

The purpose of this paper is to test the performance of the control system developed for the helicopter automatic approach and landing on the moving vessel deck, when different values of backlashes are applied to the four control actuators.

The system consists of automatic control algorithm based on the linear quadratic regulator and the vessel motion prediction algorithm based on autoregressive method with parameters calculated using Burg’s method. Necessary navigation data is provided by on-board inertial navigation system/Global Positioning System. Calculated control commands are executed by four electromechanical actuators. Performance of the mission, which is based on selected procedure of approach and landing of the helicopter on the moving vessel deck, is analyzed taking into account different values of backlashes applied to the actuators.

In this paper, a description of the control system dedicated for automatic approach and landing of the helicopter on the moving vessel deck is shown. Necessary information about helicopter dynamic model, control system and vessel motion model is included. Tests showing influence of actuator backlashes on the mission performance are presented.

The developed control methodology can be adapted for selected helicopter and used in prospective development of an automatic flight control system (AFCS) or in a simulator. The system can be used to define in which conditions helicopter can perform safe and successful automatic approach and landing on a moving vessel deck.

In this paper, an integrated control system is presented; influence of the control actuator backlashes on the mission performance is analyzed.

The purpose of this study is to test the performance of the designed automatic control system based on the Linear Quadratic Regulator (LQR) and Linear Quadratic Gaussian (LQG) algorithms during landing of the helicopter on the ship deck. This paper is a further development of the series based on Topczewski et al. (2020).

The system consists of two automatic control algorithms based on LQR and the LQG. It is integrated with the ship motion prediction system based on autoregressive algorithm with parameters calculated using Burg’s method. It is assumed that the source of necessary navigation data is integrated Inertial Navigation System with Global Positioning System. Landing of the helicopter on the ship deck is performed in automatic way, based on the preselected procedure. Performance of the control system is analyzed when all necessary navigation data is available for the system and in case when one of the parameters is unavailable during performing the procedure.

In this paper, description of the designed control system developed for performing the approach and landing of the helicopter using selected procedure is presented. Helicopter dynamic model is validated using the manufacturer data and by test pilots, overview is presented. Necessary information about ship motion model is also included. Tests showing mission performance while using LQR and LQG algorithms applied to the control system are presented and analyzed, taking into account both situations when full navigation data is available/unavailable for the control system.

Results of the system performance analyses can be used for selection of the proper control methodology for prospective helicopters autopilots. Furthermore, the system can be used to analyze the mission safety when information about one of the navigation parameters is identified by the navigation system as unavailable or incorrect and therefore unavailable during landing on the ship deck.

In this paper, control system dedicated for the automatic landing of the helicopter on the ship deck, based on two different control algorithms is presented. Influence of lack of information about one of the navigation parameters on the mission performance is analyzed.

The purpose of this paper is to elaborate and develop an automatic system for automatic flight control system (AFCS) performance evaluation. Consequently, the developed AFCS algorithm is implemented and tested in a virtual environment on one of the mission task elements (MTEs) described in Aeronautical Design Standard 33 (ADS-33) performance specification.

Control algorithm is based on the Linear Quadratic Regulator (LQR) which is adopted to work as a controller in this case. Developed controller allows for automatic flight of the helicopter via desired three-dimensional trajectory by calculating iteratively deviations between desired and actual helicopter position and multiplying it by gains obtained from the LQR methodology. For the AFCS algorithm validation, the objective data analysis is done based on specified task accomplishment requirements, reference trajectory and actual flight parameters.

In the paper, a description of an automatic flight control algorithm for small helicopter and its evaluation methodology is presented. Necessary information about helicopter dynamic model is included. The test and algorithm analysis are performed on a slalom maneuver, on which the handling qualities are calculated.

Developed automatic flight control algorithm can be adapted and used in autopilot for a small helicopter. Methodology of evaluation of an AFCS performance can be used in different applications and cases.

In the paper, an automatic flight control algorithm for small helicopter and solution for the validation of developed AFCS algorithms are presented.

Reducing inequity in health between the poor and the rich is one of the challenges of the Iranian health sector. Access to health services in Iran is lower in the lowest-income quarter, and the rich use health services more. The purpose of this study is to provide a comprehensive framework for enabling financial access by the poor to health services in Iran.

Policy options were validated and approved by experts and specialists in two stages using the Delphi technique. The sample was consisted of 22 well-known experts on the subject who were selected based on purposive sampling. To evaluate the reliability of the questionnaire, a pilot study was conducted with five participants. Dimensional validity of the policy model, which was agreed upon by more than 75% of the participants was acceptable.

The main aspects of the model were divided into five categories: identifying the poor, policymaking to prevent the aggravation of health poverty, providing targeted funding, highlighting the importance of coherent regulation and ensuring financial accessibility to health services for the poor. This model could align the activities of all stakeholders in the form of a network and considers its prerequisites.

Prevention of dire financial consequences in the case of referral to follow up the treatment alongside exemption and financial protection policies through the networking activities of organizations involved in this field is a crucial step in securing financial support for the poor. Although the researchers included a wide range of policymakers in the Delphi study to gather all perspectives about options for financially support the poor, there may be some potential neglected policy advices.