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Optimization of crop cultivation area using grasshopper algorithm with virtual water perspectives

SUSTAINABLE WATER RESOURCES MANAGEMENT 2023年第3期9卷 82页

作者： Mohammadrezapour, Omolbani Bazi, Ebrahim Zeynali, Mohammadjavad Galavi, Hadi Gorgan Univ Agr Sci & Nat Resources Gorgan Iran Univ Zabol Fac Water & Soil Dept Water Engn Zabol Iran Univ Birgand Dept Water Engn Birjand Iran

Agriculture sector is the largest water consumer among all known demands for water. Having measured the direct water consumption is only one indicator of water supplied to this sector, while the virtual water used during the production process can also stand for a large share of water being indirectly used. Therefore, considering the virtual water consumption can be a defining factor to optimize crop cultivation accordingly. To this end, this research is structured to practice optimizing crop cultivation area in Golestan province of Iran, with the objectives of maximizing green water use and conservation of water resources while maintaining the farmers' profit through the virtual water trade approach using the grasshopper optimization algorithm. The crop water demand (CWD), blue virtual water (BVW), green virtual water (GVW), and total virtual water (TVW) of 21 agricultural products were calculated in Seven categories including cereals, industrial products, beans, vegetable, cucurbits, feed plants, and rice for 13 major counties of the Golestan province for the period of 2008-2016. The optimization model was implemented for the 2015 data. Results showed that in most counties the area under cereals cultivation was declined sharply after the optimization and other products such as bean, feed plants and vegetables, etc. replaced it. In addition, in the whole province, the area under cultivation of cereal crops and rice decreased by 93% and 36%, respectively;while the area under bean and vegetables cultivation increased by 949.22% and 111.1%, respectively. The optimization process increased the farmers' profit by 46.15%, while decreasing the export of blue virtual water by 323.76 mm(3) (81.6%). Results, proved the effectiveness of the grasshopper optimization algorithm in this application and its strength in dealing with multi-objective models especially in water resources engineering. It is also concluded that the virtual water trade, being a key factor in the plant fa

关键词： Virtual water Cultivation area Optimization grasshopper algorithm

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Optimising routing using nature inspired grasshopper algorithm to improve performance of VANETs

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INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS 2024年第3-4期17卷 183-199页

作者： Gupta, Abhishek Singh, Jaspreet Chandigarh Univ Dept Comp Sci & Engn Mohali Punjab India

The paper integrates grasshopper algorithm as a bio-inspired method to improve the performance of vehicle ad hoc networks (VANETs). VANETs are highly mobile with quick topology changes and limited communication range, with a large network architecture supported by roadside units (RSUs). Thus, the need for customised routing strategies inspires the work to present modified pairing and evaluation behaviour. A unique decision-making mechanism within the grasshopper algorithm is designed and implemented. A fitness function is introduced that takes into account energy efficiency and delay for the broadcast response to evaluate the total cost including execution and idle time. The reduction of packet transmission delay forms the primary goal. The quality of service (QoS) parameters are evaluated against state-of-art algorithms to depict its significance in addressing the current challenges. The research focuses on the application of an advanced fitness function as essential elements in VANET performance optimisation using the grasshopper algorithm.

关键词： vehicular ad hoc network road side units quality of service QoS grasshopper algorithm fitness function

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Automation of 3D average human body shape modeling using Rhino and grasshopper algorithm

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FASHION AND TEXTILES 2021年第1期8卷 1-20页

作者： Lee, Kyu Sun Song, Hwa Kyung Kyung Hee Univ Dept Clothing & Text 26 Kyungheedae Ro Seoul South Korea

The aim of this study is to develop an automated process for modeling average 3D human body according to body types using both NUBRS-based modeling software Rhinoceros 3D (R) (Rhino) and grasshopper as an algorithm editor. First, we categorized men aged 36 to 55 years included in SizeUSA 3D data into the three body types (normal, overweight, and obese), and selected seven samples in each body type. To execute the automated process of generating an average 3D model of their lower bodies in a step-by-step manner, the following procedures were performed: (1) Determine the main reference lines on the 3D-scanned lower bodies, including six horizontal reference lines and six vertical reference lines;(2) Create horizontal and vertical line grids and intersection points (3) Generate an average 3D model in a position that corresponds to the average coordinates of the intersection points (vertex coordinates) of seven samples for each body type. A grasshopper algorithm was formulated to automatically execute all procedures that had to be repeatedly performed. As a way to verify the average model's size and shape, the girth measurements of the samples for each body type were averaged, and the results were compared with those of the 3D average body shape. It was found that the deviation was less than 1 cm, which indicates the validity of the 3D modeling approach applied in the present study. Each process was incorporated into commands available in the Rhino interface, and this automation allowed a number of 3D body shape modeling operations to be implemented in a significantly reduced time period.

关键词： 3D modeling grasshopper algorithm Men's lower body 3D body scan

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Simulation model and fault analysis of air circulation system of the aircraft based on grasshopper optimization algorithm: support vector machine

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SOFT COMPUTING 2023年第18期27卷 13269-13284页

作者： Wu Huiyong Jin Shuchun Jin Zhu Shenyang Univ Chem Technol Coll Sci Shenyang 110142 Liaoning Peoples R China Neusoft Corp Shenyang 110179 Liaoning Peoples R China

To effectively analyze the working state of the air circulation system of the aircraft at high altitude, it is necessary to conduct simulation analysis on the ground. In this paper, a simulated annealing-grasshopper optimization algorithmtion algorithm support vector machine is proposed to establish the overall simulation model of the circulation system of the aircraft and to conduct fault injection analysis. By introducing the support vector machine to classify the results of the system and applying of grasshopper algorithm to optimize the support vector machine with methods such as simulated annealing and position migration, the optimal parameter values can be obtained. The results indicate that the simulation system can effectively simulate the temperature changes of the aircraft in various operating states;the optimized support vector machine can effectively distinguish the fault types of the aircraft component outlet;meanwhile, the system convergence is accelerated to avoid falling into the local optimal problems.

关键词： Air circulation system control Fault analysis Support vector machine grasshopper algorithm Simulated annealing algorithm Parameter optimization

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Improved grasshopper algorithm Based on Gravity Search Operator and Pigeon Colony Landmark Operator

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IEEE ACCESS 2020年 8卷 22203-22224页

作者： Guo, S. S. Wang, J. S. Xie, W. Guo, M. W. Zhu, L. F. Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan 114044 Peoples R China

The grasshopper optimization algorithm (GOA) is a new meta-heuristic algorithm inspired by the behavior of grasshopper groups. Aiming at the shortcomings of poor development ability and low convergence accuracy of GOA, this paper introduces the gravity search operator into the optimization process of GOA to improve the grasshopper's global exploration and avoid falling into local optimum in advance. At the same time, a pigeon search operator-landmark operator is introduced to improve and balance the algorithm's exploration and development capabilities. In order to verify the validity of the improved algorithm, this paper will adopts the gravity search operator and a deterrent landmark operator hybrid grasshoppers algorithm (HGOA) with basic grasshopper algorithm (GOA), particle swarm optimization (PSO) algorithm, sine and cosine algorithm (SCA), moth-flame optimization (MFO) algorithm, salp swarm algorithm (SSA), and bat algorithm (BA) to optimize 28 test functions. And the analysis and comparison of the obtained statistical data results finally show that the proposed improved grasshopper algorithm has better optimization ability.

关键词： grasshopper algorithm gravity search operator Pigeon landmark operator function optimization

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Research on PID Parameter Self-Tuning Speed Control System Based on grasshopper Optimazation algorithm-Optimized BP Neural Network 3

Research on PID Parameter Self-Tuning Speed Control System B...

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3rd International Conference on Energy, Power and Electrical Engineering, EPEE 2023

作者： Huang, Yifan Huang, Yonghong Jiangsu University School of Electrical and Information Engineering Zhenjiang China

ISBN: (纸本)9798350318180

In response to the limitations associated with conventional PID control strategies, which rely heavily on predetermined design parameters and struggle to provide precise, stable motor speed and current control, particularly in the presence of disturbances, we have developed a novel double closed-loop DC speed regulation system. This system incorporates a self-tuning PID mechanism based on the grasshopper algorithm optimization neural network. To achieve this, we employed a Back-Propagation (BP) neural network to autonomously fine-tune the parameters of the PID control strategy. Subsequently, during the backpropagation phase of the neural network training, we harnessed the grasshopper algorithm to optimize these parameters based on a fitness function, leading to the calculation of updated weighting coefficients. Following this iterative process, the output voltage was computed using the incremental PID formula, enabling precise motor control. Remarkably, this approach reduced overshoot by 30%, all without the need for preemptive control parameter adjustments. Moreover, the rise time experienced only a marginal increase of approximately 0.06 seconds. These advancements effectively address the limitations associated with traditional PID control strategies, expanding their utility beyond narrow operational ranges and enhancing performance in complex working conditions. The outcome is a speed regulation system characterized by significantly improved accuracy and robustness, ideally suited to meet the demanding requirements of engineering applications. © 2023 IEEE.

关键词： BP neural network component grasshopper algorithm PID control Precise control Speed control system

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Automatic extraction of upper body landmarks using Rhino and grasshopper algorithms

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FASHION AND TEXTILES 2022年第1期9卷 36页

作者： Ryu, Eun Joo Song, Hwa Kyung Ewha Womans Univ Dept Fash Ind Seoul South Korea Kyung Hee Univ Dept Clothing & Text Seoul South Korea

The aim of this study is to develop algorithms for automatic landmark extraction on women with various upper body types and body inclinations using the grasshopper algorithm editor, which enables the user to interact with the 3D modeling interface. First, 15 landmarks were defined based on the morphological features of 3D body surfaces and clothing applications, from which automatic landmark extraction algorithms were developed. To verify the accuracy of the algorithms on various body shapes, this study determined criteria for key body shape factors (BMI, neck slope, upper body slope, and shoulder slope) that influence each landmark position, classified them into body shape groups and sorted the scan samples for each body type using the 6th SizeKorea database. The statistical differences between the scan-derived measurements and the SizeKorea measurements were compared, with an allowable tolerance of ISO 20685. In the case of landmarks with significant differences, the algorithm was modified. It was found that the algorithms were successfully applied to various upper body shapes, which improved the reliability and accuracy of the algorithm.

关键词： Upper body shape Landmark Automatic extraction 3D body scan grasshopper algorithm

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An improved VM selection and allocation hybrid algorithm using grasshopper and firefly in cloud computing

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INTERNATIONAL JOURNAL OF EMBEDDED SYSTEMS 2024年第3-4期17卷 251-266页

作者： Singh, Rachhpal Singh, Sarpreet Sri Guru Granth Sahib World Univ Dept Comp Sci Fatehgarh Sahib India

Cloud computing has emerged as a dynamic and resource-intensive domain, demanding innovative solutions to efficiently allocate and manage resources. In response, this paper introduces a pioneering optimisation algorithm that seamlessly integrates the grasshopper algorithm for virtual machine selection and the firefly algorithm (FA) for physical machine selection. The primary objective is to optimise critical quality of service parameters while effectively addressing challenges associated with service level agreement violation (SLA-V) and power consumption. Through a comprehensive series of rigorous evaluations, grasshopper and FA consistently outperform existing solutions. The authors demonstrate significant reduction in SLA-V and power consumption, offering tangible benefits to cloud service providers. This work represents a promising advancement in cloud resource management, aligning with green computing initiatives and promising cost-saving opportunities.

关键词： cloud computing CC resource allocation grasshopper algorithm firefly algorithm FA quality of service QoS SLA violation power consumption PC optimisation green computing cost savings

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Parametric optimization of friction stir welded ZE42 rare earth alloys using grasshopper modelling technique

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INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM 2024年第5期18卷 2843-2854页

作者： Darwins, A. K. Satheesh, M. Dhas, J. Edwin Raja Lewise, K. Anton Savio Raj, R. Ajith Manideep, B. Noorul Islam Ctr Higher Educ Dept Automobile Engn Kumaracoil 629180 India Bahrain Polytech Dept Mech Engn Isa Town Bahrain Karunya Inst Technol & Sci Dept Aerosp Engn Coimbatore 641114 India Malla Reddy Coll Engn & Technol Dept Aeronaut Engn Hyderabad India MLR Inst Technol Dept Aeronaut Engn Hyderabad Telangana India

The present work is the investigating the parametric optimization of FSW parameters for joining ZE42 magnesium alloys by multi-objective grasshopper modelling technique (MOGOA) and non-dominated sorted genetic algorithm-II (NSGA-II). Regression equations were used to predict the optimal tensile strength and hardness of the FSW joints, while tensile and Vickers hardness testing was used to obtain experimental results. Response surface method and Box-Behnken experimental design were used to create the experimental methodology, while the adequacy of the predicted and experimental results was analyzed by Analysis of variance. Five different tool types were tested for different levels of input parametric values. The optimized input parameters were 1150 rpm of tool rotation speed, 60 mm/min of welding speed, 5 kN of axial force and cylindrical threaded tool pin, which exhibited the highest ultimate tensile strength for specimen '2'. It was found that the axial force was the most influential input parameter on the output tensile strength and microhardness, followed by welding speed and the tool pin profile. It was found that the NSGA-II provided better optimization compared to MOGOA. The fractography analysis indicated ductile fracture for specimen '2', which also exhibited the highest ultimate tensile strength 180 MPa and enhanced Vickers hardness of 80.6 HV while the highest hardness noted was 84.3 HV (specimen 20) during the experimental trials.

关键词： Magnesium ZE42 alloy Parametric optimization Friction stir welding grasshopper algorithm NSGA-II Grey relational analysis Response surface methodology

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Stochastic modeling and optimization of turbogenerator performance using meta-heuristic techniques

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QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL 2024年第8期40卷 4414-4438页

作者： Sinwar, Deepak Kumar, Naveen Kumar, Ashish Saini, Monika Manipal Univ Jaipur Dept IoT & Intelligent Syst Jaipur Rajasthan India Manipal Univ Jaipur Dept Math & Stat Jaipur Rajasthan India

The objective of this paper is to identify the most sensitive component of a turbogenerator and optimize its availability. To achieve this, we begin by conducting an initial reliability, availability, maintainability, and dependability (RAMD) analysis on each component. Subsequently, a novel stochastic model is developed to analyze the steady-state availability of the turbogenerator, employing a Markov birth-death process. In this model, failure and repair rates are assumed to follow an exponential distribution and are statistically independent. To optimize the proposed stochastic model, we employ four population-based meta-heuristic approaches: the grey wolf optimization (GWO), the dragonfly algorithm (DA), the grasshopper optimization algorithm (GOA), and the whale optimization algorithm (WOA). These algorithms are utilized to find the optimal solution by iteratively improving the availability of the turbogenerator. The performance of each algorithm is evaluated in terms of system availability and execution time, allowing us to identify the most efficient algorithm for this task. Based on the numerical results, it is evident that the WOA outperforms the GWO, GOA, and DA in terms of both system availability and execution time.

关键词： dragonfly algorithm grasshopper algorithm gray wolf optimization Markov model turbogenerator thermal power plant whale optimization algorithm

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