To better regulate the speed of brushless DC motors, an improved algorithm based on original Glowworm Swarm Optimization is proposed. The proposed solves problems poor robustness, slow convergence, and low accuracy exhibited by traditional PID controllers. When selecting glowworm neighborhood set, optimization scheme growth competition behavior weeds applied to a single prevent falling into loc...

This paper presents the investigations on the application of evolutionary algorithms particle swarm optimization (PSO) and invasive weed optimization (IWO) to find approximate solutions of optimal control problems. For this purpose, discrete form of the problem is converted to a quasi assignment problem, considering a partition of the time-control space. The approximate optimal control function...

Abstract The present study proposes a novel framework to optimize the reservoir operation through linking mesohabitat hydraulic modeling and metaheuristic optimization mitigate environmental impact at downstream of reservoir. Environmental function was developed by simulation. Then, utilized in structure optimization. Different algorithms including practice swarm optimization, invasive weed dif...

With the fast increase of the documents, using Text Document Classification (TDC) methods has become a crucial matter. This paper presented a hybrid model of Invasive Weed Optimization (IWO) and Naive Bayes (NB) classifier (IWO-NB) for Feature Selection (FS) in order to reduce the big size of features space in TDC. TDC includes different actions such as text processing, feature extraction, form...

The social, economic, and environmental impacts of invasive plants are well recognized. However, these variable impacts are rarely accounted for in the spatial prioritization of funding for weed management. We examine how current spatially explicit prioritization methods can be extended to identify optimal budget allocations to both eradication and control measures of invasive species to minimi...

One of the effectual text classification approaches for learning extensive information is incremental learning. The big issue that occurs enhancing accuracy, as comprised a large number terms. In order to address this issue, new approach designed using proposed hybrid optimization algorithm named Henry Fuzzy Competitive Multi-verse Optimizer (HFCVO)-based Deep Maxout Network (DMN). Here, optima...

Minimum cross-entropy is widely used in image segmentation for its effectiveness. However, when the algorithm applied to multi-threshold segmentation, there are some problems such as large amount of calculation, time-consuming and poor practicability due exhaustive search optimal threshold. Therefore, this paper, a hybrid whale optimization (IWOA) which incorporates (WOA) invasive weed (IWO) pr...

This paper proposes designing of Static Synchronous Series Compensator (SSSC) based damping controller to enhance the stability of a Single Machine Infinite Bus (SMIB) system by means of Invasive Weed Optimization (IWO) technique. Conventional PI controller is used as the SSSC damping controller which takes rotor speed deviation as the input. The damping controller parameters are tuned based on...

Evolutionary Algorithms (EAs) are a fascinating branch of computational intelligence with much potential for use in many application areas. The fundamental principle of EAs is to use ideas inspired by the biological mechanisms observed in nature, such as selection and genetic changes, to find the best solution for a given optimization problem. Generally, EAs use iterative processes, by growing ...