the vast use of linear prediction coefficients (lpc) in speech processing systems has intensified the importance of their accurate computation. this paper is concerned with computing lpc coefficients using evolutionary algorithms: genetic algorithm (ga), particle swarm optimization (pso), dif-ferential evolution (de) and particle swarm optimization with differentially perturbed velocity (pso-dv...

human language, over its evolutionary history, has emerged as one of the fundamental defining characteristic of the modern man. however, this milestone evolutionary process through natural selection has not left any ’linguistic fossils’ that may enable us to trace back the actual course of development of language and its establishment in human societies. lacking analytical tools to fathom the cr...

Oil production from tight oil reservoirs has become economically feasible because of the combination horizontal drilling and multistage hydraulic fracturing. Optimal fracture design plays a critical role in successful economical reservoir. However, many complex parameters such as spacing half-length make fracturing treatments costly uncertain. To improve design, it is essential to determine rea...

Deep learning is becoming an increasingly interesting and powerful machine learning method with successful applications in many domains, such as natural language processing, image recognition, and hand-written character recognition. Despite of its eminent success, limitations of traditional learning approach may still prevent deep learning from achieving a wide range of realistic learning tasks...

Advances in supervised learning with deep neural networks have enabled robust classification in many real world domains. An interesting question is if such advances can also be leveraged effectively for computational creativity. One insight is that because evolutionary algorithms are free from strict requirements of mathematical smoothness, they can exploit powerful deep learning representation...

the imperialist competitive algorithm (ica) that was recently introduced has shown its good performance in optimization problems. this algorithm is inspired by competition mechanism among imperialists and colonies, in contrast to evolutionary algorithms. this paper presents optimization of bead geometry in welding process using of ica. therefore, two case studies from literature are presented t...

Many evolutionary algorithms for assembly sequence planning (ASP) have been researched. But those algorithms have lots of blind searching because individuals have little consideration about geometry and assembly process information of product in the evolutionary process. To improve individuals' intelligence and decrease blind searching, motivated by the self-assembly computing and multi-agent e...

In this paper, a new clustering algorithm based on CLA-EC is proposed. The CLA-EC is a model obtained by combining the concepts of cellular learning automata and evolutionary algorithms. The CLA-EC is used to search for cluster centers in such a way that minimizes the squared-error criterion. The simulation results indicate that the proposed algorithm produces clusters with acceptable quality w...

Designing artiicial neural networks (ANNs) for different applications has been a key issue in the ANN eld. Although there are many training algorithms available for learning ANN's connection weights, algorithms which can learn ANN's architectures are relatively few. At present, ANN design still relies heavily on human experts who have suucient knowledge about ANNs and the problem to be solved. ...