In this paper, we explore the application of Opt-AiNet, an immune network approach for search and optimisation problems, to learning qualitative models in the form of qualitative differential equations. The Opt-AiNet algorithm is adapted to qualitative model learning problems, resulting in the proposed system QML-AiNet. The potential of QML-AiNet to address the scalability and multimodal search...

Feature selection is of great importance in Quantitative Structure-Activity Relationship (QSAR) analysis. This problem has been solved using some meta-heuristic algorithms such as: GA, PSO, ACO, SA and so on. In this work two novel hybrid meta-heuristic algorithms i.e. Sequential GA and LA (SGALA) and Mixed GA and LA (MGALA), which are based on Genetic algorithm and learning automata for QSAR f...

Introduction: Beam-angle optimization (BAO) is a computationally intensive problem for a number of reasons. First, the search space of the solutions is huge, requiring enumeration of all possible beam orientation combinations. For example, when choosing 4 angles out of 36 candidate beam angles, C36 = 58905 possible combinations exist.  Second, any change in a   beam 4 config...

introduction: amajor problem in the treatment of cancer is the lack of an appropriate method for the early diagnosis of the disease. the chemical reaction within an organ may be reflected in the form of proteomic patterns in the serum, sputum, or urine. laser mass spectrometry is a valuable tool for extracting the proteomic patterns from biological samples. a major challenge in extracting such ...

t his paper presents a new feature selection approach for automatically extracting   ms lesions in 3d mr images. presented method is applicable to different types of ms lesions. in this method, t1, t2 and flair images are firstly preprocessed. in the next phase, effective features to extract ms lesions are selected by using a genetic algorithm. the fitness function of the genetic algorithm is t...

This research discusses intrusion detection systems based on computer networks and a model for the detection of malware using artificial immune system (AIS). The SIA has three main theories: the clonal selection, negative selection and network theory. This work used the ClonalG algorithm developed by Castro & Timmis (2002) [5] and implemented in Weka 3.6.4 for the intrusions detection in the KD...

Natural selection works on variation in fitness, but how should we measure "variation" to predict the rate of future evolution? Fisher's fundamental theorem of natural selection provides the short-run answer: the instantaneous rate of growth of a population's mean fitness is its variance in fitness. This identity captures an important feature of the evolutionary process, but, because it does no...