The integration of an approximate model and a clonal selection algorithm (CSA) is considered as one of the most effective ways to solve complex optimization design problems in engineering. In this study, first, a process for developing an approximate model and the principles of clonal selection algorithms is presented. Second, a variotherm temperature injection mold was used to produce a large ...

High dimensional pose state space is the main challenge in articulated human motion tacking. In this paper, we propose a novel generative approach in the framework of artificial immune model, by which we try to widen the bottleneck with effective search strategy embedded in the extracted state subspace. Firstly, we learn the latent space of pose state and propose a manifold reconstruction metho...

A series of acquired immunity inspired clonal selection models have previously been proposed that includes principle model components and base (single repertoire) models. Also previously proposed is a contrived problem domain called ‘colour space’ and a number of scenarios intended for the investigation of adaptive models. This work units these two (until now) isolated streams of work by realiz...

Artificial immune systems are a kind of new computational intelligence methods which draw inspiration from the human immune system. Most immune system inspired optimization algorithms are based on the applications of clonal selection and hypermutation, and known as clonal selection algorithms. These clonal selection algorithms simulate the immune response process based on principles of Darwinia...

—The energy consumption is considered as key factors of green cloud computing to achieve resource allocation. To address the issue of high energy consumption and low efficiency of cloud computing, this paper proposes a powerefficient immune clonal optimization algorithm (PEICO) based on dynamic load balancing strategy and immune clonal selection theory in green cloud computing. The experimenta...

Wireless Sensor Networks (WSN) are emerging as a new tier within the IT scheme and a rich domain of active analysis involving hardware and system design, networking, and programming models, data management, security and social actors. Wireless sensor networks are compared with wired networks are additional well vulnerable to attacks and intrusions. The intrusion detection is outlined as a mecha...

Both the clonal selection algorithm (CSA) and the ant colony optimization (ACO) are inspired by natural phenomena and are effective tools for solving complex problems. CSA can exploit and explore the solution space parallely and effectively. However, it can not use enough environment feedback information and thus has to do a large redundancy repeat during search. On the other hand, ACO is based...

A clonal selection algorithm (Clonalg) inspires from Clonal Selection Principle used to explain the basic features of an adaptive immune response to an antigenic stimulus. It takes place in various scientific applications and it can be also used to determine the membership functions in a fuzzy system. The aim of the study is to adjust the shape of membership functions and a novice aspect of the...

Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means ...

Unsupervised classification algorithm based on clonal selection principle named Unsupervised Clonal Selection Classification (UCSC) is proposed in this paper. The new proposed algorithm is data driven and self-adaptive, it adjusts its parameters to the data to make the classification operation as fast as possible. The performance of UCSC is evaluated by comparing it with the well known K-means ...