Related papers: Cuckoo Search: State-of-the-Art and Opportunities
Cuckoo search (CS) is a relatively new algorithm, developed by Yang and Deb in 2009, and CS is efficient in solving global optimization problems. In this paper, we review the fundamental ideas of cuckoo search and the latest developments as…
Cuckoo search (CS) was introduced in 2009, and it has attracted great attention due to its promising efficiency in solving many optimization problems and real-world applications. In the last few years, many papers have been published…
A new metaheuristic optimisation algorithm, called Cuckoo Search (CS), was developed recently by Yang and Deb (2009). This paper presents a more extensive comparison study using some standard test functions and newly designed stochastic…
Many optimization problems in science and engineering are highly nonlinear, and thus require sophisticated optimization techniques to solve. Traditional techniques such as gradient-based algorithms are mostly local search methods, and often…
In this paper, we intend to formulate a new metaheuristic algorithm, called Cuckoo Search (CS), for solving optimization problems. This algorithm is based on the obligate brood parasitic behaviour of some cuckoo species in combination with…
The notions of dominating sets of graphs began almost 400 years ago with the game of chess, which sparked the analysis of dominating sets of graphs, at first relatively loosely until the beginnings of the 1960s, when the issue was given…
Clustering of web search result document has emerged as a promising tool for improving retrieval performance of an Information Retrieval (IR) system. Search results often plagued by problems like synonymy, polysemy, high volume etc.…
This work aims to investigate the reliability of software products as an important attribute of computer programs; it helps to decide the degree of trustworthiness a program has in accomplishing its specific functions. This is done using…
The cuckoo filter data structure of Fan, Andersen, Kaminsky, and Mitzenmacher (CoNEXT 2014) performs the same approximate set operations as a Bloom filter in less memory, with better locality of reference, and adds the ability to delete…
Segmentation of medical images is an essential part in the process of diagnostics. Physicians require an automatic, robust and valid results. Hidden Markov Random Fields (HMRF) provide powerful model. This latter models the segmentation…
In this modern era a great deal of metamorphism is observed around us which eventuate due to some minute modifications and innovations in the area of Science and Technology. This paper deals with the application of a meta heuristic…
Context: Software has become an innovative solution nowadays for many applications and methods in science and engineering. Ensuring the quality and correctness of software is challenging because each program has different configurations and…
The growing interest in cybersecurity has significantly increased articles designing and implementing various Cyber Deception (CYDEC) mechanisms. This trend reflects the urgent need for new strategies to address cyber threats effectively.…
With huge design spaces for unique chemical and mechanical properties, we remove a roadblock to computational design of {high-entropy alloys} using a metaheuristic hybrid Cuckoo Search (CS) for "on-the-fly" construction of Super-Cell Random…
Cuckoo hashing is a common hashing technique, guaranteeing constant-time lookups in the worst case. Adding a stash was proposed by Kirsch, Mitzenmacher, and Wieder at SICOMP 2010, as a way to reduce the probability of failure (i.e., the…
Image Segmentation is a technique of partitioning the original image into some distinct classes. Many possible solutions may be available for segmenting an image into a certain number of classes, each one having different quality of…
Although cuckoo hashing has significant applications in both theoretical and practical settings, a relevant downside is that it requires lookups to multiple locations. In many settings, where lookups are expensive, cuckoo hashing becomes a…
A new hybridization of the Cuckoo Search (CS) is developed and applied to optimize multi-cell solar systems; namely multi-junction and split spectrum cells. The new approach consists of combining the CS with the Nelder-Mead method. More…
Though effective in the segmentation, conventional multilevel thresholding methods are computationally expensive as exhaustive search are used for optimal thresholds to optimize the objective functions. To overcome this problem,…
Identifying similar documents within extensive volumes of data poses a significant challenge. To tackle this issue, researchers have developed a variety of effective distributed computing techniques. With the advancement of computing power…