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The purpose of this paper is to use an ABC algorithm to improve the thrust–torque ratio of a rotating-wing unmanned aerial vehicle (UAV) model.

The design of UAVs, such as aircraft, drones, helicopters, has become one of the popular engineering areas with the development of technology. This study aims to improve the value of thrust–torque ratio of an unmanned helicopter. For this purpose, an unmanned helicopter was built at the Faculty of Aeronautics and Astronautics, Erciyes University. The maximum thrust–torque ratio was calculated considering the blade length, blade chord width, blade mass density and blade twist angle. For calculation, artificial bee colony (ABC) algorithm was used. By using ABC algorithm, the maximum thrust–torque ratio was obtained against the optimum input values. For this purpose, a model with four inputs and a single output is formed. In the generated system model, optimum thrust–torque ratio was calculated by changing the input values used in the ±5% range. As a result of this study, approximately 31% improvement was achieved. According to these results, the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV.

According to these results, approximately 31% improvement was achieved, and the proposed approach will provide convenience to the designers in the design of the rotating-wing UAV.

It takes a long time to obtain the optimum thrust–torque ratio value through the ABC algorithm method.

Using ABC algorithm provides to improve the value of thrust–torque ratio of an unmanned helicopter. With this algorithm, unmanned helicopter flies more than ever. Thus, the presented method based on the ABC algorithm is more efficient.

The application of the ABC algorithm method can be used effectively to calculate the thrust–torque ratio in UAV.

Providing an original and penetrating a method that saves time and reduces the cost to improve the value of thrust–torque ratio of an unmanned helicopter.

The purpose of this paper is to present a novel approach based on the artificial bee colony (ABC) algorithm aiming to achieve maximum acceleration and maximum endurance for morphing unmanned aerial vehicle (UAV) design.

Some of the most important issues in the design of UAV are the design of thrust system and determination of the endurance of the UAV. Although propeller selection is very important for the thrust system design, battery selection has the utmost importance for the determination of UAV endurance. In this study, the calculations of maximum acceleration and endurance required by ZANKA-II during the flight are considered simultaneously. For this purpose, a model based on the ABC algorithm is proposed for the morphing UAV design, aiming to achieve the maximum acceleration and endurance. In the proposed model, the propeller diameter, propeller pitch and battery values used in morphing UAV's power system design are selected as the input parameters; maximum acceleration and endurance are selected as the output parameters. To obtain the maximum acceleration and endurance, the optimum input parameters are determined through the ABC algorithm-based model.

Considerable improvements on maximum acceleration and endurance of morphing UAV with ABC algorithm-based model are obtained.

The endurance and acceleration due to the thrust are two separate parameters that are not normally proportional to each other. In this study, optimization of UAV’s endurance and acceleration is considered with equal importance.

Using artificial intelligence techniques causes fast and simple optimization for determination of UAV’s endurance and acceleration with equal importance. In the simulation studies with ABC algorithm, satisfactory results are obtained.

The results of the study have showed that the proposed approach could be an alternative method for UAV designers.

Providing a new and efficient method saves time and reduces cost in calculations of maximum acceleration and endurance of the UAV.

The purpose of this paper is to increase flight performance of small unmanned aerial vehicle (UAV) using simultaneous UAV and autopilot system design.

A small UAV is manufactured in Erciyes University, College of Aviation, Model Aircraft Laboratory. Its wing and tail is able to move forward and backward in the nose-to-tail direction in prescribed interval. Autopilot parameters and assembly position of wing and tail to fuselage are simultaneously designed to maximize flight performance using a stochastic optimization method. Results are obtained are used for simulations.

Using simultaneous UAV and autopilot system design idea, flight performance is maximized.

Permission of Directorate General of Civil Aviation in Turkey is required for testing UAVs in long range.

Simultaneous design idea is very beneficial for improving UAV flight performance.

Creating a novel method to improve flight performance of UAV and developing an algorithm performing simultaneous design idea.

The purpose of this paper is to present a novel approach based on the differential search (DS) algorithm integrated with the adaptive network-based fuzzy inference system (ANFIS) for unmanned aerial vehicle (UAV) winglet design.

The winglet design of UAV, which was produced at Faculty of Aeronautics and Astronautics in Erciyes University, was redesigned using artificial intelligence techniques. This approach proposed for winglet redesign is based on the integration of ANFIS into the DS algorithm. For this purpose, the cant angle (c), the twist angle (t) and taper ratio (λ) of winglet are selected as input parameters; the maximum value of lift/drag ratio (E_max) is selected as the output parameter for ANFIS. For the selected input and output parameters, the optimum ANFIS parameters are determined by the DS algorithm. Then the objective function based on optimum ANFIS structure is integrated with the DS algorithm. With this integration, the input parameters for the E_max value are obtained by the DS algorithm. That is, the DS algorithm is used to obtain both the optimization of the ANFIS structure and the necessary parameters for the winglet design. Thus, the UAV was reshaped and the maximum value of lift/drag ratio was calculated based on new design.

Considerable improvements on the max E are obtained through winglet redesign on morphing UAVs with artificial intelligence techniques.

It takes a long time to obtain the optimum E_max value by the computational fluid dynamics method.

Using artificial intelligence techniques saves time and reduces cost in maximizing E_max value. The simulation results showed that satisfactory E_max values were obtained, and an optimum winglet design was achieved. Thus, the presented method based on ANFIS and DS algorithm is faster and simpler.

The application of artificial intelligence methods could be used in designing more efficient aircrafts.

The study provides a new and efficient method that saves time and reduces cost in redesigning UAV winglets.

The purpose of this paper is to rise the autonomous flight performance of the small unmanned aerial vehicle (UAV) using simultaneous tailplane of UAV and autopilot system design.

A small UAV is remanufactured in the UAV laboratory. Its tailplane can be changed before the flight. Autopilot parameters and some parameters of tailplane are instantaneously designed to maximize autonomous flight performance using a stochastic optimization method. Results found are applied for simulations.

Benefitting simultaneous tailplane of UAV and autopilot system design process, autonomous flight performance is maximized.

Authorization of Directorate General of Civil Aviation in Turkey is required for UAV flights.

Simultaneous tailplane and autopilot system design process is so useful for refining UAV autonomous flight performance.

Simultaneous tailplane and autopilot system design process fulfills confidence, high autonomous performance, and easy service demands of UAV users. By that way, UAV users will be able to use better UAVs.

Creating a novel technique to recover autonomous flight performance (e.g. less overshoot, less settling time and less rise time during trajectory tracking) of UAV and developing a novel procedure performing simultaneous tailplane of UAV and autopilot system design idea.

This study aims to analyze the theoretical complexity that underlies purchase managers’ perceptions of their ability to take part in the implementation of a new back-office service strategy.

A survey of purchasing department managers in the Antalya (Turkey) region was conducted. The purchasing managers of Antalya’s five-star accommodation businesses comprise the research sample.

Within the scope of the study, 205 questionnaires were gathered. Factor analysis, correlation and regression analysis were applied to the obtained data. The learning organization (LO) consists of three factors (organization, group/team and individual), service innovation (SI) consists of two factors (employee innovation behavior and new service development) and technology acceptance (TA) consists of four factors (perceived usefulness, perceived ease of use, facilitating situations and social factors), according to the findings of the factor analysis. According to correlation analysis, LO, SI and TA all have positive and significant relationships. The LO has been observed to play an intermediary function in the relationship between TA and SI as a consequence of the analysis that determines the mediation effect.

This study which dealt with the dimensions of SI, TA and LO showed a proposed model which gives a better understanding of how the development of back-office system strategies is affected by LOs.

The purpose of this research paper is to establish the impact of process and service innovation on non-financial and financial performance in the tourism sector, as well as to explain the mediating role of organizational learning.

A quantitative approach was used, based on partial least squares–structural equation modeling (PLS-SEM), Smart PLS 4.0 software. The sample consisted of 426 establishments in the tourism sector in Zone I, Ecuador. Online surveys were employed to collect data, yielding 118 responses, to assess the impact of innovation on business performance from 2020 to 2022.

Process and service innovation positively and significantly affect non-financial and financial performance, respectively. Organizational learning mediates the relationship between process innovation and disservice. The relationship between non-financial and financial performance could not be confirmed. The model explains 53.10% of non-financial performance and 26.10% of financial performance.

The relationship between innovation and performance in the tourism sector has been studied in several developed economies, while little has been studied in developing countries. This work contributes to an empirical discussion including a mediating variable in the innovation–performance relationship in the Latin American context.

El propósito de esta investigación es establecer el impacto de la innovación de procesos y servicios en el desempeño no financiero y financiero en el sector turístico, así como explicar el papel mediador del aprendizaje organizacional.

Se utilizó un enfoque cuantitativo, basado en el software PLS SE M, Smart PLS 4.0. La muestra estuvo constituida por 426 establecimientos del sector turístico de la Zona I, Ecuador. Se aplicaron encuestas en línea para recopilar datos, que arrojaron 118 respuestas, para evaluar el impacto de la innovación en el desempeño empresarial de 2020 a 2022.

La innovación de proceso y de servicio afecta positiva y significativa al desempeño no financiero y financiero, respectivamente. El aprendizaje organizacional media la relación entre innovación de proceso y des servicio. No se pudo confirmar la relación entre desempeño no financiero y financiero. El modelo explica el 53.10% del desempeño no financiero y el 26.10 del desempeño financiero.

La relación entre innovación y rendimiento en el sector turístico se ha estudiado en varias economías desarrolladas, mientras que en los países en desarrollo se ha estudiado poco. Este trabajo contribuye a una discusión empírica incluyendo una variable mediadora en la relación innovación-desempeño en contexto latinoamericano.