This work presents a cost-effective base station deployment model based on artificial immune systems. It uses a multiobjective algorithm based on artificial immune systems (MOAIS) as an optimiser. MO-AIS algorithms are a new class of evolutionary algorithms. The Binary-coded Multi-objective Optimisation Algorithm (BRMOA) is inspired by the clonal selection theory and the immune network theory. ...

 Artificial immune system (AIS) approaches, which are used in this work, are learning and optimization methods that can be applied to find the solution of many types of optimization problems. This paper presents an AIS approach applied to optimize the design of an incremental discrete variable structure controller (VSC) for minimizing the generalized minimum variance (GMV) strategy. Control de...

In this paper, a metaheuristic inspired on the T-Cell model of the immune system (i.e., an artificial immune system) is introduced. The proposed approach (called DTC, for Dynamic T-Cell) is used to solve dynamic optimization problems, and is validated using test problems taken from the specialized literature on dynamic optimization. Results are compared with respect to artificial immune approac...

A machine-learning algorithm based on the natural immune system metaphor has been developed, AINE (Artificial Immune Network). AINE developed from initial work on Artificial Immune Systems for data analysis, for which detailed experimentation was undertaken as to the affect of altering algorithm parameters had on the behaviour of the system. Two of the parameters, the network affinity threshold...

Vehicle routing problems are well-known combinational optimization problems with considerable economic significance. Considering the vehicle routing problem with limited capacity on tree is a problem that often naturally arises in railway, river, and rural road networks. In this paper, we describe an artificial immune system that is distributed, robust, dynamic, diverse and adaptive. It capture...

Artificial immune systems (AIS) are a computational metaphor based on biological implementations of immune systems. Natural immune systems are capable of performing computation based on several properties that they possess. Immune systems are capable of adapting to new stimuli – they respond appropriately to novel stimuli, and they can remember previous encounters with stimuli. The processes wh...

Constructing a precise classifier is an important issue in pattern recognition task. Combination the decision of several competing classifiers to achieve improved classification accuracy has become interested in many research areas. In this study, Artificial Immune System (AIS) as an effective artificial intelligence technique was used for designing of several efficient classifiers. Combination...

Artificial Immune Systems have been used successfully to build recommender systems for film databases. In this research, an attempt is made to extend this idea to web site recommendation. A collection of more than 1000 individuals’ web profiles (alternatively called preferences / favourites / bookmarks file) will be used. URLs will be classified using the DMOZ (Directory Mozilla) database of th...

The job shop scheduling problem (JSSP) is a notoriously difficult problem in combinatorial optimization. This paper presents a hybrid artificial immune system for the JSSP with the objective of minimizing makespan. The proposed approach combines the artificial immune system, which has a powerful global exploration capability, with the local search method, which can exploit the optimal antibody....

BACKGROUND There is a high risk of tuberculosis (TB) disease diagnosis among conventional methods. OBJECTIVES This study is aimed at diagnosing TB using hybrid machine learning approaches. MATERIALS AND METHODS Patient epicrisis reports obtained from the Pasteur Laboratory in the north of Iran were used. All 175 samples have twenty features. The features are classified based on incorporatin...