R. Thenmozhi¹, Abdul Wahid Nasir², Vijaya Krishna Sonthi³, T. Avudaiappan⁴, Seifedine Kadry⁵, Kuntha Pin⁶, Yunyoung Nam^7,*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 2037-2051, 2022, DOI:10.32604/cmc.2022.022203 - 03 November 2021

Abstract Wireless sensor networks (WSN) comprise a set of numerous cheap sensors placed in the target region. A primary function of the WSN is to avail the location details of the event occurrences or the node. A major challenge in WSN is node localization which plays an important role in data gathering applications. Since GPS is expensive and inaccurate in indoor regions, effective node localization techniques are needed. The major intention of localization is for determining the place of node in short period with minimum computation. To achieve this, bio-inspired algorithms are used and node localization… More >

Fabián Riquelme^1,*, Rodrigo Olivares¹, Francisco Muñoz¹, Xavier Molinero³, Maria Serna²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6305-6321, 2022, DOI:10.32604/cmc.2022.021804 - 11 October 2021

Abstract An influence game is a simple game represented over an influence graph (i.e., a labeled, weighted graph) on which the influence spread phenomenon is exerted. Influence games allow applying different properties and parameters coming from cooperative game theory to the contexts of social network analysis, decision-systems, voting systems, and collective behavior. The exact calculation of several of these properties and parameters is computationally hard, even for a small number of players. Two examples of these parameters are the length and the width of a game. The length of a game is the size of its smaller… More >

Mustafa Abdul Salam^1,*, Ahmad Taher Azar², Rana Hussien²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6339-6363, 2022, DOI:10.32604/cmc.2022.020583 - 11 October 2021

Abstract Extreme Learning Machine (ELM) is popular in batch learning, sequential learning, and progressive learning, due to its speed, easy integration, and generalization ability. While, Traditional ELM cannot train massive data rapidly and efficiently due to its memory residence, high time and space complexity. In ELM, the hidden layer typically necessitates a huge number of nodes. Furthermore, there is no certainty that the arrangement of weights and biases within the hidden layer is optimal. To solve this problem, the traditional ELM has been hybridized with swarm intelligence optimization techniques. This paper displays five proposed hybrid Algorithms… More >

Omar Almomani^*

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 409-429, 2021, DOI:10.32604/cmc.2021.016113 - 22 March 2021

Abstract Network Intrusion Detection System (IDS) aims to maintain computer network security by detecting several forms of attacks and unauthorized uses of applications which often can not be detected by firewalls. The features selection approach plays an important role in constructing effective network IDS. Various bio-inspired metaheuristic algorithms used to reduce features to classify network traffic as abnormal or normal traffic within a shorter duration and showing more accuracy. Therefore, this paper aims to propose a hybrid model for network IDS based on hybridization bio-inspired metaheuristic algorithms to detect the generic attack. The proposed model has… More >

Oday Ali Hassen¹, Sarmad Omar Abter², Ansam A. Abdulhussein³, Saad M. Darwish^4,*, Yasmine M. Ibrahim⁴, Walaa Sheta⁵

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 961-981, 2021, DOI:10.32604/cmc.2021.014404 - 22 March 2021

Abstract Medical image segmentation has consistently been a significant topic of research and a prominent goal, particularly in computer vision. Brain tumor research plays a major role in medical imaging applications by providing a tremendous amount of anatomical and functional knowledge that enhances and allows easy diagnosis and disease therapy preparation. To prevent or minimize manual segmentation error, automated tumor segmentation, and detection became the most demanding process for radiologists and physicians as the tumor often has complex structures. Many methods for detection and segmentation presently exist, but all lack high accuracy. This paper’s key contribution… More >

Aolin Sun, Xiang Cao^*, Xu Xiao, Liwen Xu

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 551-564, 2021, DOI:10.32604/iasc.2021.01008 - 18 January 2021

Abstract An essential issue in a target search is safe navigation while quickly finding targets. In order to improve the efficiency of a target search and the smoothness of AUV’s (Autonomous Underwater Vehicle) trajectory, a fuzzy-based bio-inspired neural network approach is proposed in this paper. A bio-inspired neural network is applied to a multi-AUV target search, which can effectively plan search paths. In the meantime, a fuzzy algorithm is introduced into the bio-inspired neural network to make the trajectory of AUV obstacle avoidance smoother. Unlike other algorithms that need repeated training in the parameters selection, the More >

Xiang Cao^1,2,*, Ling Chen¹, Liqiang Guo³, Wei Han⁴

Intelligent Automation & Soft Computing, Vol.27, No.2, pp. 391-407, 2021, DOI:10.32604/iasc.2021.01002 - 18 January 2021

Abstract As one of the classical problems in autonomous underwater vehicle (AUV) research, path planning has obtained a lot of research results. Many studies have focused on planning an optimal path for AUVs. These optimal paths are sometimes too close to obstacles. In the real environment, it is difficult for AUVs to avoid obstacles according to such an optimal path. To solve the safety problem of AUV path planning in a dynamic uncertain environment, an algorithm combining a bio-inspired neural network and potential field is proposed. Based on the environmental information, the bio-inspired neural network plans More >

Masood Ahmad¹, Fasee Ullah^2,*, Ishtiaq Wahid¹, Atif Khan³, M. Irfan Uddin⁴, Abdullah Alharbi⁵, Wael Alosaimi⁵

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 321-336, 2021, DOI:10.32604/cmc.2021.014102 - 12 January 2021

Abstract Internet of Everything (IoE) indicates a fantastic vision of the future, where everything is connected to the internet, providing intelligent services and facilitating decision making. IoE is the collection of static and moving objects able to coordinate and communicate with each other. The moving objects may consist of ground segments and flying segments. The speed of flying segment e.g., Unmanned Ariel Vehicles (UAVs) may high as compared to ground segment objects. The topology changes occur very frequently due to high speed nature of objects in UAV-enabled IoE (Ue-IoE). The routing maintenance overhead may increase when… More >

Phong Thanh Nguyen¹, Vy Dang Bich Huynh², Khoa Dang Vo¹, Phuong Thanh Phan¹, Mohamed Elhoseny³, Dac-Nhuong Le^4,5,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2555-2571, 2021, DOI:10.32604/cmc.2021.012941 - 28 December 2020

Abstract Data fusion is a multidisciplinary research area that involves different domains. It is used to attain minimum detection error probability and maximum reliability with the help of data retrieved from multiple healthcare sources. The generation of huge quantity of data from medical devices resulted in the formation of big data during which data fusion techniques become essential. Securing medical data is a crucial issue of exponentially-pacing computing world and can be achieved by Intrusion Detection Systems (IDS). In this regard, since singular-modality is not adequate to attain high detection rate, there is a need exists… More >

Zhigang Deng^1,*, Zhenzhong Chu², Zaman Mohammed Tousif³

Intelligent Automation & Soft Computing, Vol.26, No.6, pp. 1503-1515, 2020, DOI:10.32604/iasc.2020.010798 - 24 December 2020

Abstract Trajectory tracking control can be considered as one of the main researches of unmanned underwater vehicles (UUV). The bio-inspired neurodynamics model was used to make the output continuous and smooth for the inflection points to deal with the speed jump of the conventional tracking controller for discrete trajectories. A horizon-plane trajectory tracking control law is designed using the bio-inspired neurodynamics model and sliding-mode method without chattering. Finally, the simulation of the mentioned two methods is compared with the results showing this as effective and feasible. More >