Back scattering response from single, finite and infinite array of nonlinear antennas based on intelligent water drops algorithm

Author(s):  
Amir Bahrami ◽  
Saeed Reza Ostadzadeh

Purpose The purpose of this paper is to calculate the back scattering response from single, finite and infinite arrays of nonlinear antennas like the case where the antennas are exposed to high-value signals such as lightning strokes. Design/methodology/approach In this paper, the authors have used a recently introduced optimization technique called intelligent water drop. Findings The results exhibit that the method used by the authors is faster and more accurate than other conventional optimization algorithms, i.e. particle swarm optimization and genetic algorithm. Originality/value A new optimization algorithm is used to solve nonlinear problem accurately and sufficiently. Although the technique is not confined to the mentioned examples in the paper, it can be applied to other nonlinear circuits.

2014 ◽  
Vol 13 (10) ◽  
pp. 5075-5084 ◽  
Author(s):  
Bashar Abedal Mohdi AlDeeb ◽  
Norita Md Norwawi ◽  
Mohammed A. Al-Betar

In the optimization areas, there are different algorithms that have been applied such as swarm intelligence algorithms. The researchers have found different algorithms by simulating the behaviors of various swarms of insects and animals such as fishes, bees, and ants. The intelligent water drops algorithm is one of the recently developed algorithms in the swarm intelligence field; this algorithm mimicked the dynamic of river systems. The natural water drops used to develop Intelligent Water Drop (IWD) algorithm. Therefore, the mechanisms that happen in rivers have inspired the researchers mainly to create new algorithms. IWD is a population-based algorithm where each drop represents a solution and the sharing between the drops during the search lead to a better drops (or solutions). This paper presents recent developments of the IWD algorithms in terms of theory and application. This paper concludes many of research directions that are necessary for the future of IWD algorithm.


Author(s):  
Bashar A. Aldeeb ◽  
Mohammed Azmi Al-Betar ◽  
Norita Md Norwawi ◽  
Khalid A. Alissa ◽  
Mutasem K. Alsmadi ◽  
...  

2020 ◽  
Vol 38 (5/6) ◽  
pp. 997-1011
Author(s):  
Ning Li ◽  
Parthasarathy R. ◽  
Harshila H. Padwal

Purpose Smart mobility is a major guideline in the development of Smart Cities’ transport systems and management. The issue of transition into green, secure and sustainable transport modes, such as using bicycles, should be implemented in this case, along with the subjectivism of management. Design/methodology/approach The proposed technology reflects the Smart Bicycle vehicle model, which tracks cyclists and weather conditions and turns to electric motors in critical circumstances. Findings This reduces the physical load and battery consumption of cyclists which affects the Smart Cities’ ecology positively. Originality/value In Smart Vehicle Bicycle Communication Transport, the vehicle movement optimization technique is used for traffic scenarios to analyze traffic signaling systems that give better results in variable and dense traffic conditions.


Author(s):  
Rahul Bisht ◽  
Afzal Sikander

Purpose This paper aims to achieve accurate maximum power from solar photovoltaic (PV), its five parameters need to be estimated. This study proposes a novel optimization technique for parameter estimation of solar PV. Design/methodology/approach To extract optimal parameters of solar PV new optimization technique based on the Jellyfish search optimizer (JSO). The objective function is defined based on two unknown variables and the proposed technique is used to estimate the two unknown variables and the rest three unknown variables are estimated analytically. Findings In this paper, JSO is used to estimate the parameters of a single diode PV model. In this study, eight different PV panels are considered. In addition, various performance indices, such as PV characteristics, such as power-voltage and current-voltage curves, relative error (RE), root mean square error (RMSE), mean absolute error (MAE) and normalized mean absolute error (NMAE) are determined using the proposed algorithm and existing algorithms. The results for different solar panels have been obtained under varying environmental conditions such as changing temperature and constant irradiance or changing irradiance and constant temperature. Originality/value The proposed technique is new and provides better results with minimum RE, RMSE, NMAE, MAE and converges fast, as depicted by the fitness graph presented in this paper.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Aayush Bhat ◽  
Vyom Gupta ◽  
Savitoj Singh Aulakh ◽  
Renold S. Elsen

Purpose The purpose of this paper is to implement the generative design as an optimization technique to achieve a reasonable trade-off between weight and reliability for the control arm plate of a double-wishbone suspension assembly of a Formula Student race car. Design/methodology/approach The generative design methodology is applied to develop a low-weight design alternative to a standard control arm plate design. A static stress simulation and a fatigue life study are developed to assess the response of the plate against the loading criteria and to ensure that the plate sustains the theoretically determined number of loading cycles. Findings The approach implemented provides a justifiable outcome for a weight-factor of safety trade-off. In addition to optimal material distribution, the generative design methodology provides several design outcomes, for different materials and fabrication techniques. This enables the selection of the best possible outcome for several structural requirements. Research limitations/implications This technique can be used for applications with pre-defined constraints, such as packaging and loading, usually observed in load-bearing components developed in the automotive and aerospace sectors of the manufacturing industry. Practical implications Using this technique can provide an alternative design solution to long periods spent in the design phase, because of its ability to generate several possible outcomes in just a fraction of time. Originality/value The proposed research provides a means of developing optimized designs and provides techniques in which the design developed and chosen can be structurally analyzed.


Author(s):  
Ram Kumar ◽  
Afzal Sikander

Purpose This paper aims to suggest the parameter identification of load frequency controller in power system. Design/methodology/approach The suggested control approach is established using fuzzy logic to design a fractional order load frequency controller. A new suitable control law is developed using fuzzy logic, and based on this developed control law, the unknown parameters of the fractional order proportional integral derivative (FOPID) controller are derived using an optimization technique, which is being used by minimizing the integral square error. In addition, to confirm the effectiveness of the proposed control design approach, numerous simulation tests were carried out on an actual single-area power system. Findings The obtained results reveal the superiority of the suggested controller as compared to the recently developed controllers with regard to time response specifications and quantifiable indicators. Additionally, the potential of the suggested controller is also observed by improving the load disturbance rejections under plant parametric uncertainty. Originality/value To the best of the authors’ knowledge, the work is not published anywhere else.


1960 ◽  
Vol 9 (2) ◽  
pp. 175-182 ◽  
Author(s):  
K. N. Dodd

A Theory is developed, based on the very limited available experimental evidence, to predict the distortion and disintegration of a water drop when it is exposed to a stream of air with continuously increasing relative velocity. The theory is applied to water drops situated in the path of a solid sphere moving through the air.


2018 ◽  
Vol 35 (9) ◽  
pp. 2052-2079 ◽  
Author(s):  
Umamaheswari E. ◽  
Ganesan S. ◽  
Abirami M. ◽  
Subramanian S.

Purpose Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues. Design/methodology/approach The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS. Findings As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique. Originality/value As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.


2018 ◽  
Vol 2018 ◽  
pp. 1-8
Author(s):  
Zi Yan Liu ◽  
Pan Mao ◽  
Li Feng ◽  
Shi Mei Liu

Appropriate resource allocation has great significance to enhance the energy efficiency (EE) for cooperative communication system. The objective is to allocate the resource to maximize the energy efficiency in single-cell multiuser cooperative communication system. We formulate this problem as subcarrier-based resource allocation and solve it with path planning in graph theory. A two-level neural network model is designed, in which the users and subcarrier are defined as network nodes. And then we propose an improved intelligent water drops algorithm combined with Genetic Algorithm; boundary condition and initialization rules of path soil quantity are put forward. The simulation results demonstrate that the proposed resource allocation scheme can effectively improve the energy efficiency and enhance QoS performance.


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