The justification for having chosen an ES as opposed to other evolutionary algorithms was simply that the proposed AES uses floating-point numbers to encode the continuous variables used in the differential equations, whereas genetic algorithms typically encode binary variables. An evolutionary programming...
Feature selection is a crucial preprocessing technique that enhances the efficiency and accuracy of machine learning models by removing irrelevant and redundant features, thus reducing computational complexity and storage costs. However, existing binary swarm intelligence algorithms often encounter challenges suc...
Machine Learning algorithms that perform classification are increasingly been adopted in Information and Communication Technology (ICT) systems and infrast
Genetic algorithms may be used for fault-based testing where faults associated with mistakes in branch predicates are revealed. The software has been deliberately seeded with faults in the branch predicates (i.e. mutation testing), and our system successfully killed 97% of the mutants....
Voting Strategy In subject area: Computer Science A voting strategy in computer science refers to a widely used method that obtains a final result by combining multiple base clustering partitions through majority rule. It ensures stability and represents the consensus among the base partitions, although...
The increasing complexity and high-dimensional nature of real-world optimization problems necessitate the development of advanced optimization algorithms. Traditional Particle Swarm Optimization (PSO) often faces challenges such as local optima entrapmen
Lifetime is defined as the time until one of the participating nodes runs out of energy; also, the stochastic sensor model is used in this research. In practice, a WSN is divided into multiple sub-regions for easy layout, organization, and management. Since the stochastic sensor model is ...
In relevance feedback algorithms, selective sampling is often used to reduce the cost of labeling and explore the unlabeled data. In this paper, we propose... C Jian,K Wang - 《Pattern Recognition》 被引量: 164发表: 2007年 SVM-based active feedback in image retrieval using clustering and ...
Compressive sensing is favored because it breaks through the constraints of Nyquist sampling law in signal reconstruction. However, the security defects of joint compression encryption and the problem of low quality of reconstructed image restoration nee
The other element used in this guide is abusiness modelessence. Shortly, I’ve been looking for a way to summarize the key elements of any business in a couple of lines of text: ABusiness ModelEssence according to FourWeekMBA is a way to find the critical characteristics of any business ...