invasiveweedoptimization (IWO) algorithm a kind of stochastic optimizationalgorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in nature. The ...
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ISBN:
(纸本)9781728158556
invasiveweedoptimization (IWO) algorithm a kind of stochastic optimizationalgorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in nature. The classical IWO algorithm has the problem that it is easy to fall into the local optimum, which will lead to the low precision. An new improved IWO algorithm based on the differential evolution operators was proposed to solve the one-dimensional bin packing (BP) problem. The proposed differential evolution invasiveweedoptimization (DE-IWO) algorithm, the genetic algorithm (GA), the firefly algorithm (FA) and the IWO algorithm are used to solve the three bin packing problems with different sizes. The simulation results verify the effectiveness of the proposed algorithm.
invasiveweedoptimization(IWO) algorithm a kind of stochastic optimizationalgorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in *** classical...
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invasiveweedoptimization(IWO) algorithm a kind of stochastic optimizationalgorithm to simulate the weeds propagation phenomena based on the characteristics of weeds and the swarm behavior of plants in *** classical IWO algorithm has the problem that it is easy to fall into the local optimum,which will lead to the low *** new improved IWO algorithm based on the differential evolution operators was proposed to solve the one-dimensional bin packing(BP) *** proposed differential evolution invasiveweedoptimization(DE-IWO) algorithm,the genetic algorithm(GA),the firefly algorithm(FA) and the IWO algorithm are used to solve the three bin packing problems with different *** simulation results verify the effectiveness of the proposed algorithm.
This article presents the study of frequency regulation of a solar energy based two area integrated power system equipped with multi-staged PID & conventional PID controller. To optimize the parameters of the proj...
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This article presents the study of frequency regulation of a solar energy based two area integrated power system equipped with multi-staged PID & conventional PID controller. To optimize the parameters of the projected multi-staged PID controllers, invasive weed optimization algorithm (IWOA) is employed. A disturbance to the extent of 0.01 p.u. is injected to the control area 1 to examine the effectiveness of the controllers in maintaining the system stability. Comparison of the results with respect to the magnitude of oscillations and settling time indicates that the proposed multi-staged PID controller outperforms the classical PID controller. The projected multi-staged PID controller optimised by the aforesaid algorithm (IWOA) helps in attaining nominal values of the tie-line power & frequency deviations during large parametric variation of the system and variation of system condition. Robustness of the proposed control strategy is established under various conditions such as (i) inclusion of a time delay of 0.7 s in each control area, (ii) wide variations of the system parameters and (iii) application of a random loading pattern in area 1.
The article deals with the regulation of frequency comprising of interconnected dual area solar thermal system by employing PID and multi staged PID controller as secondary controller. A recently invented evolutionary...
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ISBN:
(纸本)9781538659823
The article deals with the regulation of frequency comprising of interconnected dual area solar thermal system by employing PID and multi staged PID controller as secondary controller. A recently invented evolutionary algorithm called invasive weed optimization algorithm (IWOA) technique is used to tune the constraints of recommended controllers. To verify the supremacy of the controller a disturbance of 0.01 p.u. in control area-1 and a time delay of 0.7sec was introduced in both the areas. Investigation suggests that multi staged PID controller performs better in terms of settling time and magnitude of oscillation as compared to traditional PID controller. IWOA optimized multi staged PID controller attain the nominal values during large alteration in system condition and parameters.
According to the problem of the optimization of overall performance of idle spectrum assignment for cognitive radio, it proposed a spectrum assignment method for cognitive radio based on binary weedalgorithm. Conside...
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According to the problem of the optimization of overall performance of idle spectrum assignment for cognitive radio, it proposed a spectrum assignment method for cognitive radio based on binary weedalgorithm. Considering maximizing total network efficiency and fair effectiveness as a criterion, the algorithm is designed and implementation steps are presented. Simulation and analysis compares the solution of the spectrum assignment with Genetic algorithm and particle swarm algorithm. The results show that the spectrum assignment algorithm based on binary invasiveweedalgorithm has a higher performance. It can achieve maximizing sum reward and proportional fair better and receiving a better optimal solution.
This study deals with optimal resources planning of energy resources in smart home energy system (SHES), where PV (Photovoltaic) panel, battery and electrical heater (EH) are employed to meet all electrical and therma...
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ISBN:
(纸本)9781509049882
This study deals with optimal resources planning of energy resources in smart home energy system (SHES), where PV (Photovoltaic) panel, battery and electrical heater (EH) are employed to meet all electrical and thermal demands. The advantage of this configuration is avoiding the use of two different energy carriers including electricity and natural gas in downstream users, in addition, reduction of SHES operation cost. An energy management controller (EMC) based on invasiveweedoptimization (IWO) algorithm is designed in order to optimize the energy routing and scheduling of different resources to obtain an efficient look-up table, by which the power generation of each energy resource is determined for all hourly time intervals. Different electricity tariffs and all operational constraints of energy resources are considered. Several scenarios are defined and the impacts of system components on SHES operation cost are investigated. Moreover, feasibility study of the proposed SHES based on different electricity and gas prices is conducted. It is observed that the proposed optimal scheduling based on IWO algorithm outperforms other approaches. Furthermore, it is shown that self-discharge rate of the battery, affects the system operational performance, especially time of charging and discharging of the battery.
The paper proposes a procedure for solving the inverse Stefan problem consisted in reconstruction of the function describing the heat transfer coefficient on the basis of temperature measurements. Elaborated method is...
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The paper proposes a procedure for solving the inverse Stefan problem consisted in reconstruction of the function describing the heat transfer coefficient on the basis of temperature measurements. Elaborated method is based on two procedures: solution of the appropriate direct Stefan problem by using the finite difference method combined with the alternating phase truncation method and minimization of some functional with the aid of invasive weed optimization algorithm. For verifying the effectiveness of investigated algorithm the experimental data obtained in the solidification of aluminum are used.
How to select the suitable parameters and kernel model is a very important problem for Twin Support Vector Machines (TSVMs). In order to solve this problem, one solving algorithm called invasiveweedoptimization Algo...
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How to select the suitable parameters and kernel model is a very important problem for Twin Support Vector Machines (TSVMs). In order to solve this problem, one solving algorithm called invasive weed optimization algorithm for Optimizating the Parameters of Mixed Kernel Twin Support Vector Machines (IWO-MKTSVMs) is proposed in this paper. Firstly, introducing the mixed kernel, the twin support vector machines based on mixed kernel is constructed. This strategy is a good way to solve the kernel model selection. In order to solve the parameters selection problem which contain TSVMs parameters and mixed kernel model parameters, invasive weed optimization algorithm (IWO) is introduced. IWO is an optimizationalgorithm who has strong robustness and good global searching ability. Finally, compared with the classical TSVMs, the experimental results show that IWO-MKTSVMs have higher classification accuracy.
Distribution Network Reconfiguration (DNR) and optimal placement of Distributed Generators (DGs) are two major approaches to reduce losses of distribution networks. In this paper a new method to reduce network loss wi...
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ISBN:
(纸本)9781479930395;9781479930388
Distribution Network Reconfiguration (DNR) and optimal placement of Distributed Generators (DGs) are two major approaches to reduce losses of distribution networks. In this paper a new method to reduce network loss with the simultaneous utilize of these two issues is presented. For this purpose, the DNR and determining sizing and sitting of DG is modeled as an optimization problem for minimizing the total loss of the system considering operation constraints. An evolutionary algorithm called invasiveweedoptimization (IWO) algorithm is used to solve this problem. Moreover, the graph theory and tree condition for a graph are used for radiality checking during the DNR problem solution. The proposed method is applied to both IEEE 33-Bus radial test system and Khoram Abad city real network. Assessment all optimization results show the effectiveness of the proposed method for loss reduction.
In view of the problem of high energy consumption and high control costs caused by uneven airflow distribution and unreasonable control in complex mine ventilation networks, this study takes the minimum ventilation en...
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In view of the problem of high energy consumption and high control costs caused by uneven airflow distribution and unreasonable control in complex mine ventilation networks, this study takes the minimum ventilation energy consumption and number of regulators as optimization objectives to establish a multi-objective optimization model for airflow distribution in mine ventilation networks. Based on the roadway adjustable attributes and the minimum spanning tree principle, the location of regulators was reasonably determined. Moreover, this article proposes an improved invasiveweedoptimization (IIWO) algorithm to solve the optimization model with high coupling and nonlinearity. Compared with other algorithms, IIWO showed excellent optimization performance. IIWO was applied to optimize the airflow distribution in the mine ventilation network. The results show that the algorithm can effectively reduce the energy consumption and number of regulators of the ventilation network, and the energy saving rate of the fan is 31.78%.
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