Aspects of the formation of a tractor fleet of agricultural enterprises

Studies and production experience show that with an increase in the mass and power-weight factor of tractors, the return on investment in this technical progress field decreases. The paper justifies that at the current stage, the priority is to reduce the energy consumption of mechanized processes and comply with agro-technological requirements in the changing natural and production conditions. It reflects the areas of designing tractors and the effectiveness of their operation. The compaction effect on the soil is shown, taking into account the types of movers. The authors propose to complete the tractor fleet for various agro-industrial organizations.

Power Management of Hybrid Grid System With Battery Deprivation Cost Using Artificial Neural Network

Continuous power supply in an integrated electric system supplied by solar energy and battery storage can be optimally maintained with the use of diesel generators. This article discusses the optimum setting-point for isolated wind, photo-voltaic, diesel, and battery storage electric grid systems. Optimal energy supply for hybrid grid systems means that the load is sufficient for 24 h. This study aims to integrate the battery deprivation costs and the fuel price feature in the optimization model for the hybrid grid. In order to count charge–discharge cycles and measure battery deprivation, the genetic algorithm concept is utilized. To solve the target function, an ANN-based algorithm with genetic coefficients can also be used to optimize the power management system. In the objective function, a weight factor is proposed. Specific weight factor values are considered for simulation studies. On the algorithm actions, charging status, and its implications for the optimized expense of the hybrid grid, the weight factor effect is measured.

Relativistic Fractional-Dimension Gravity

This paper presents a relativistic version of Newtonian Fractional-Dimension Gravity (NFDG), an alternative gravitational model recently introduced and based on the theory of fractional-dimension spaces. This extended version—Relativistic Fractional-Dimension Gravity (RFDG)—is based on other existing theories in the literature and might be useful for astrophysical and cosmological applications. In particular, in this work, we review the mathematical theory for spaces with non-integer dimensions and its connections with the non-relativistic NFDG. The Euler–Lagrange equations for scalar fields can also be extended to spaces with fractional dimensions, by adding an appropriate weight factor, and then can be used to generalize the Laplacian operator for rectangular, spherical, and cylindrical coordinates. In addition, the same weight factor can be added to the standard Hilbert action in order to obtain the field equations, following methods used for scalar-tensor models of gravity, multi-scale spacetimes, and fractional gravity theories. We then apply the field equations to standard cosmology and to the Friedmann-Lemaître-Robertson-Walker metric. Using a suitable weight vtt, depending on the synchronous time t and on a single time-dimension parameter αt, we extend the Friedmann equations to the RFDG case. This allows for the computation of the scale factor at for different values of the fractional time-dimension αt and the comparison with standard cosmology results. Future additional work on the subject, including studies of the cosmological late-time acceleration, type Ia supernovae data, and related dark energy theory will be needed to establish this model as a relativistic alternative theory of gravity.

An Efficient Discrete Wavelet Transform Based Hybrid Image Watermarking Algorithm Using Human Visual Model

More than ever with growing of multimedia technology, the digital data are exchanged in the internet, which can be duplicated by unauthorized users. To avoid this problem the watermarking technology has brought this paper. Performance improvement with compare to existing algorithm is obtained by proposing a new watermarking algorithm based on Human Visual Model (HVM) and Discrete Wavelet Transform (DWT) for securing the digital data and copyright protection. DWT is applied to the input image and at each level of DWT sub bands to embed a watermark image in selected coefficients of the sub band. HVM integrate the weight factor effect of human visualization by considering into the eye’s vision is less sensitivity area, depending on brightness, frequency band and texture areas of the image sub band. In the proposed approach robustly and imperceptibly, DWT and HVM are used for obtainable weight factor, according to human eye perceptual and to determine the optimal strength at which the threshold to embedding reaches the perceptual invisibility of watermarked image to various attacks. Performance is evaluated such as Peak Signal to Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Quality Index (QI) is used to evaluate and achieve the imperceptible watermarked image. Results of PSNR values of hybrid image watermarking are between 49.73db to 36.24db. Experimental results show that our hybrid image watermarking process has enhanced robustness and displays the effectiveness of presenting images watermarking system.

Reverse guidance butterfly optimization algorithm integrated with information cross-sharing

Aiming at the disadvantages of slow convergence and the premature phenomenon of the butterfly optimization algorithm (BOA), this paper proposes a modified BOA (MBOA) called reverse guidance butterfly optimization algorithm integrated with information cross-sharing. First, the quasi-opposition concept is employed in the global search phase that lacks local exploitation capabilities to broaden the search space. Second, the neighborhood search weight factor is added in the local search stage to balance exploration and exploitation. Finally, the information cross-sharing mechanism is introduced to enhance the ability of the algorithm to jump out of the local optima. The proposed MBOA is tested in fourteen benchmark functions and three constrained engineering problems. The series of experimental results indicate that MBOA shows better performance in terms of convergence speed, convergence accuracy, stability as well as robustness.

A new Xin'anjiang and Sacramento combined rainfall-runoff model and its application

The Xin'anjiang model and the Sacramento model are two widely used short-term watershed rainfall-runoff forecasting models, each with their own unique model structure, strengths, weaknesses and applicability. This paper introduces a weight factor to integrate the two models into a combined model, and uses the cyclic coordinate method to calibrate the weight factor and the parameters of the two models to explore the possibility of the complementarity between the two models. With application to the Yuxiakou watershed in Qingjiang River, it is verified that the cyclic coordinate method, although simple, can converge rapidly to a satisfactory calibration accuracy, mostly after two iterations. Also, the results in case studies show that the forecast accuracy of the new combined rainfall-runoff model can improve the forecast precision by 4.3% in a testing period, better in runoff process fitting than the Xin'anjiang model that performs better than the Sacramento model. HIGHLIGHT This paper introduces a weight factor to integrate the two models into a combined model, and uses the cyclic coordinate method to calibrate the weight factor. it is verified that the cyclic coordinate method can converge fast to a satisfactory calibration accuracy. The results show that the forecast accuracy of the new combined rainfall-runoff model can improve the forecast precision.

Energy Efficient SWIPT Based Mobile Edge Computing Framework for WSN-Assisted IoT

With the increasing deployment of IoT devices and applications, a large number of devices that can sense and monitor the environment in IoT network are needed. This trend also brings great challenges, such as data explosion and energy insufficiency. This paper proposes a system that integrates mobile edge computing (MEC) technology and simultaneous wireless information and power transfer (SWIPT) technology to improve the service supply capability of WSN-assisted IoT applications. A novel optimization problem is formulated to minimize the total system energy consumption under the constraints of data transmission rate and transmitting power requirements by jointly considering power allocation, CPU frequency, offloading weight factor and energy harvest weight factor. Since the problem is non-convex, we propose a novel alternate group iteration optimization (AGIO) algorithm, which decomposes the original problem into three subproblems, and alternately optimizes each subproblem using the group interior point iterative algorithm. Numerical simulations validate that the energy consumption of our proposed design is much lower than the two benchmark algorithms. The relationship between system variables and energy consumption of the system is also discussed.

Modified Dynamically-updated Weighted Opportunity Cost Based Algorithm for Unbalanced Transportation Problem

Recently, Weighted Opportunity Cost (WOC) based algorithms are developed for solving balanced Transportation Problems (TPs). The exceptionality of the WOC based approaches is to introduce supply and demand as weight factor to cost entries for the control of flow of allocations. But in the unbalanced TP, there exist a pitfall whenever balancing the TP with zero dummy transportation cost as done in existing classical approaches, so that the total cost is unaffected due to dummy transportations. A modified dynamically-updated weighted opportunity cost-based algorithm embedded on Least Cost Method (LCM) is proposed which is suitable for both balanced and unbalanced TPs. Numerical instances have been carried out to demonstrate the effectiveness and efficiency of the proposed method. It is observed that, the proposed modified dynamically-updated weighted opportunity cost-based algorithm sometimes outperforms for the LCM as well as the existing weighted opportunity cost-based algorithm in unbalanced TPs. Journal of Engineering Science 12(2), 2021, 119-131