B. Kalpana¹, S. Dhanasekaran², T. Abirami³, Ashit Kumar Dutta⁴, Marwa Obayya⁵, Jaber S. Alzahrani⁶, Manar Ahmed Hamza^7,*

Computer Systems Science and Engineering, Vol.44, No.3, pp. 2243-2257, 2023, DOI:10.32604/csse.2023.027129 - 01 August 2022

Abstract Biomedical data classification has become a hot research topic in recent years, thanks to the latest technological advancements made in healthcare. Biomedical data is usually examined by physicians for decision making process in patient treatment. Since manual diagnosis is a tedious and time consuming task, numerous automated models, using Artificial Intelligence (AI) techniques, have been presented so far. With this motivation, the current research work presents a novel Biomedical Data Classification using Cat and Mouse Based Optimizer with AI (BDC-CMBOAI) technique. The aim of the proposed BDC-CMBOAI technique is to determine the occurrence of diseases… More >

B. Chellapraba^1,*, D. Manohari², K. Periyakaruppan³, M. S. Kavitha⁴

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 2353-2366, 2023, DOI:10.32604/iasc.2023.029923 - 19 July 2022

Abstract Hyperspectral (HS) image classification is a hot research area due to challenging issues such as existence of high dimensionality, restricted training data, etc. Precise recognition of features from the HS images is important for effective classification outcomes. Additionally, the recent advancements of deep learning (DL) models make it possible in several application areas. In addition, the performance of the DL models is mainly based on the hyperparameter setting which can be resolved by the design of metaheuristics. In this view, this article develops an automated red deer algorithm with deep learning enabled hyperspectral image (HSI)… More >

R. Rengaraj alias Muralidharan^1,*, K. Latha²

Intelligent Automation & Soft Computing, Vol.35, No.2, pp. 1923-1937, 2023, DOI:10.32604/iasc.2023.029495 - 19 July 2022

Abstract In cloud computing (CC), resources are allocated and offered to the clients transparently in an on-demand way. Failures can happen in CC environment and the cloud resources are adaptable to fluctuations in the performance delivery. Task execution failure becomes common in the CC environment. Therefore, fault-tolerant scheduling techniques in CC environment are essential for handling performance differences, resource fluxes, and failures. Recently, several intelligent scheduling approaches have been developed for scheduling tasks in CC with no consideration of fault tolerant characteristics. With this motivation, this study focuses on the design of Gorilla Troops Optimizer Based… More >

Soma Prathibha^1,*, Deepak Dahiya², C. R. Rene Robin³, Cherukuru Venkata Nishkala⁴, S. Swedha⁵

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 199-214, 2023, DOI:10.32604/iasc.2023.025819 - 06 June 2022

Abstract Thyroid disease is a medical condition caused due to the excess release of thyroid hormone. It is released by the thyroid gland which is in front of the neck just below the larynx. Medical pictures such as X-rays and CT scans can, however, be used to diagnose it. In this proposed model, Deep Learning technology is used to detect thyroid diseases. A Convolution Neural Network (CNN) based modified ResNet architecture is employed to detect five different types of thyroid diseases namely 1. Hypothyroid 2. Hyperthyroid 3. Thyroid cancer 4. Thyroiditis 5. Thyroid nodules. In the… More >

Ahmed M. Agwa¹, Mohamed Abdeen², Shaaban M. Shaaban^1,3,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5525-5541, 2022, DOI:10.32604/cmc.2022.031580 - 28 July 2022

Abstract In this study, a bald eagle optimizer (BEO) is used to get optimal parameters of the fractional-order proportional–integral–derivative (FOPID) controller for load frequency control (LFC). Since BEO takes only a very short time in finding the optimal solution, it is selected for designing the FOPID controller that improves the system stability and maintains the frequency within a satisfactory range at different loads. Simulations and demonstrations are carried out using MATLAB-R2020b. The performance of the BEO-FOPID controller is evaluated using a two-zone interlinked power system at different loads and under uncertainty of wind and solar energies.… More >

Nashwa Nageh¹, Ahmed Elshamy¹, Abdel Wahab Said Hassan¹, Mostafa Sami², Mustafa Abdul Salam^3,4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5245-5268, 2022, DOI:10.32604/cmc.2022.030906 - 28 July 2022

Abstract Team Formation (TF) is considered one of the most significant problems in computer science and optimization. TF is defined as forming the best team of experts in a social network to complete a task with least cost. Many real-world problems, such as task assignment, vehicle routing, nurse scheduling, resource allocation, and airline crew scheduling, are based on the TF problem. TF has been shown to be a Nondeterministic Polynomial time (NP) problem, and high-dimensional problem with several local optima that can be solved using efficient approximation algorithms. This paper proposes two improved swarm-based algorithms for… More >

Abdulaziz S. Alghamdi^1,*, Randa Alharbi², Suliman A. Alsuhibany³, Sayed Abdel-Khalek^4,5

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2865-2878, 2022, DOI:10.32604/cmc.2022.028088 - 16 June 2022

Abstract Security is a vital parameter to conserve energy in wireless sensor networks (WSN). Trust management in the WSN is a crucial process as trust is utilized when collaboration is important for accomplishing trustworthy data transmission. But the available routing techniques do not involve security in the design of routing techniques. This study develops a novel statistical analysis with dingo optimizer enabled reliable routing scheme (SADO-RRS) for WSN. The proposed SADO-RRS technique aims to detect the existence of attacks and optimal routes in WSN. In addition, the presented SADO-RRS technique derives a new statistics based linear More >

Krishan Arora¹, Gyanendra Prasad Joshi², Mahmoud Ragab^3,4,5,*, Muhyaddin Rawa^6,7,8, Ahmad H. Milyani^6,7, Romany F. Mansour⁹, Eunmok Yang¹⁰

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3165-3180, 2022, DOI:10.32604/cmc.2022.026966 - 16 June 2022

Abstract Reestablishment in power system brings in significant transformation in the power sector by extinguishing the possession of sound consolidated assistance. However, the collaboration of various manufacturing agencies, autonomous power manufacturers, and buyers have created complex installation processes. The regular active load and inefficiency of best measures among varied associates is a huge hazard. Any sudden load deviation will give rise to immediate amendment in frequency and tie-line power errors. It is essential to deal with every zone’s frequency and tie-line power within permitted confines followed by fluctuations within the load. Therefore, it can be proficient… More >

D. Karthik Prabhu^1,*, R. V. Maheswari², B. Vigneshwaran²

Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1441-1454, 2022, DOI:10.32604/iasc.2022.024128 - 25 May 2022

Abstract Measurement and recognition of Partial Discharge (PD) in power apparatus is considered a protuberant tool for condition monitoring and assessing the state of a dielectric system. During operating conditions, PD may occur either in the form of single and multiple patterns in nature. Currently, for PD pattern recognition, deep learning approaches are used. To evaluate spatial order less features from the large-scale patterns, a pre-trained network is used. The major drawback of traditional approaches is that they generate high dimensional data or requires additional steps like dictionary learning and dimensionality reduction. However, in real-time applications,… More >

Dong An¹, Junqing Jia¹, Wenchao Cai¹, Deyu Yang¹, Chao Lv¹, Jiawei Zhu², Yingying Jiao^3,*

Energy Engineering, Vol.119, No.4, pp. 1531-1545, 2022, DOI:10.32604/ee.2022.019284 - 23 May 2022

Abstract This paper develops a real-time PV arrays maximum power harvesting scheme under partial shading condition (PSC) by reconfiguring PV arrays using Aquila optimizer (AO). AO is based on the natural behaviors of Aquila in capturing prey, which can choose the best hunting mechanism ingeniously and quickly by balancing the local exploitation and global exploration via four hunting methods of Aquila: choosing the searching area through high soar with the vertical stoop, exploring in different searching spaces through contour flight with quick glide attack, exploiting in convergence searching space through low flight with slow attack, and More > Graphic Abstract