1. Flowchart of Cuckoo Optimization Algorithm. which there is no human expertise. Even though human expertise should be used when it is needed and available; it often proves less adequate for automated problem-
CSBHC has 10 main steps illustrated as a flowchart in Fig. 3 and described as follows: Step 1 Initialize problem and CSBHC parameters. In this step, the optimization problem is usually modeled as min{f(x)|x∈X} or max{f(x)|x∈X}, where f(x) is the objective function of the ...
Fig. 2. Flowchart of the proposed method. 5. Results and discussion To demonstrate the superiority of the CSA method, extensive simulations are carried out for various test cases. For simulations a dedicated software program is developed in MATLAB by considering standard IEEE 33-bus and 136-bus...
We propose a new method, named cuckoo search epistasis (CSE) for identifying significant epistatic interactions in population-based association studies with a case–control design. This method combines a computationally efficient Bayesian scoring function with an evolutionary-based heuristic search algorithm...
The flowchart of the proposed CHHO–CS method is represented in Fig. 3. The pseudo-code of the proposed CHHO–CS method is illustrated in Algorithm 3. Here is important to mention that for SVM and feature selection, in the CHHO–CS each solution of the population is encoded as a set ...
As per the above description, the harmony search/cuckoo search (HS/CS) can be given in Algorithm 1 and its corre- sponding flowchart is shown in Fig. 1. the methods are implemented under the same conditions as shown in Wang et al. (2014a). The benchmark functions described in Table ...
Fig. 4. Flowchart of summary representation. 4. Cuckoo search based multi-document summarizer Cuckoo search (CS) is one of latest meta heuristic algorithm, inspired by the species of bird called the Cuckoo. Cuckoos are fascinating birds because of their aggressive reproduction strategy and beautiful...
Figure 7 displays the flowchart of the CSO MPPT algorithm. A flying squirrel search optimization (FSSO) approach Analyzing the FSS optimization technique. The flying squirrel search approach emulates the active seeking behavior of southern FSs and the floating movements of southern squirrels who...
The results showed that the proposed algorithm achieves better results. Conclusion The proposed method, an improved version of the BM25 algorithm, utilizes both co-word implementation and Cuckoo Search, which has been verified achieving better results on a large number of experimental sets. Besides, ...
Figure 4. Flowchart of the optimization process. 4.1. Initialization In the initialization phase, the CS algorithm initializes a set of solutions which are randomly sampled from the search space. For this purpose, the dimension of the solution and the length of the population must be defined. ...