The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In this paper, a novel metaheuristic search algorithm inspired by rhinoceros' natural behaviour is proposed, namely Rhinoceros Search Algorithm (RSA). Similar to our earlier version called Elephant Search Algorithm, RSA simplifies certain habitual characteristics and stream line the search operations, thereby reducing the number of operational parameters required to configure the model. Via computer...
Elephant Search Algorithm (ESA) is one of the contemporary metaheuristic search recently proposed. Its efficacy depends largely on the right choice of gender ratio that balances the proportion between the number of male and female elephants as search agents with different functions. The male elephants are responsible for global exploration, roaming to new dimensions of search space. The female elephants...
Nature-inspired computing algorithms (NICs in short) inherit a certain length of history tracing back to Genetic Algorithm and Evolutionary Computing in the 50’s. Since February 2008 by the birth of Firefly Algorithm, NICs started to receive lots of attentions from researchers around the global. Variants and even new species of NIC algorithms boomed like sprouts after rain. While it may be disputable...
The purpose of classification in medical informatics is to predict the presence or absence of a particular disease as well as disease types from historical data. Medical data often contain irrelevant features and noise, and an appropriate subset of the significant features can improve classification accuracy. Therefore, researchers apply feature selection to identify and remove irrelevant and redundant...
Finding an appropriate set of features from data of high dimensionality for building an accurate classification model is a well-known NP-hard computational problem. Unfortunately in data mining, some big data are not only big in volume but they are described by a large number of features. Many feature subset selection algorithms have been proposed in the past, they are nevertheless far from perfect...
In computer science, a computational challenge exists in finding a globally optimized solution from a tremendously large search space. Heuristic optimization methods have therefore been created that can search the very large spaces of candidate solutions. These methods have been extensively studied in the past, and progressively extended in order to suit a wide range of optimization problems. Researchers...
Traveling Salesman Problem (TSP) is a classical problem of optimization for researchers and its modeling is of great interest for Engineering, Operations Research and Computer Science. For solving TSP, many methods have been proposed, including heuristic ones. Our work extends the hybrid model, based on Particle Swarm Optimization, Genetic Algorithms and Fast Local Search, for the symmetric blind...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.