Broderick Crawford^1,*, Ricardo Soto¹, Hanns de la Fuente Mella¹, Claudio Elortegui¹, Wenceslao Palma¹, Claudio Torres-Rojas¹, Claudia Vasconcellos-Gaete², Marcelo Becerra¹, Javier Peña¹, Sanjay Misra³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4295-4318, 2022, DOI:10.32604/cmc.2022.023068 - 14 January 2022

Abstract Currently, the industry is experiencing an exponential increase in dealing with binary-based combinatorial problems. In this sense, metaheuristics have been a common trend in the field in order to design approaches to solve them successfully. Thus, a well-known strategy consists in the use of algorithms based on discrete swarms transformed to perform in binary environments. Following the No Free Lunch theorem, we are interested in testing the performance of the Fruit Fly Algorithm, this is a bio-inspired metaheuristic for deducing global optimization in continuous spaces, based on the foraging behavior of the fruit fly, which… More >

Muhammad Asif Saleem¹, Muhammad Aamir^{1,2, * ,*}, Rosziati Ibrahim¹, Norhalina Senan¹, Tahir Alyas³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 6053-6067, 2022, DOI:10.32604/cmc.2022.022215 - 14 January 2022

Abstract Plant disease classification based on digital pictures is challenging. Machine learning approaches and plant image categorization technologies such as deep learning have been utilized to recognize, identify, and diagnose plant diseases in the previous decade. Increasing the yield quantity and quality of rice forming is an important cause for the paddy production countries. However, some diseases that are blocking the improvement in paddy production are considered as an ominous threat. Convolution Neural Network (CNN) has shown a remarkable performance in solving the early detection of paddy leaf diseases based on its images in the fast-growing More >

Ayman Altameem¹, Sandeep Kumar², Ramesh Chandra Poonia³, Abdul Khader Jilani Saudagar^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177 - 14 January 2022

Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes More >

Harsh Goud¹, Prakash Chandra Sharma², Kashif Nisar³, Ag. Asri Ag. Ibrahim^3,*, Muhammad Reazul Haque⁴, Narendra Singh Yadav², Pankaj Swarnkar⁵, Manoj Gupta⁶, Laxmi Chand⁶

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4409-4423, 2022, DOI:10.32604/cmc.2022.019217 - 14 January 2022

Abstract CSTR (Continuous stirred tank reactor) is employed in process control and chemical industries to improve response characteristics and system efficiency. It has a highly nonlinear characteristic that includes complexities in its control and design. Dynamic performance is compassionate to change in system parameters which need more effort for planning a significant controller for CSTR. The reactor temperature changes in either direction from the defined reference value. It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature, and deviation from reference values may cause… More >

K. Babu^1,*, C. Kumar², C. Kannaiyaraju³

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 317-329, 2022, DOI:10.32604/iasc.2022.023756 - 05 January 2022

Abstract Facial expression for different emotional feelings makes it interesting for researchers to develop recognition techniques. Facial expression is the outcome of emotions they feel, behavioral acts, and the physiological condition of one’s mind. In the world of computer visions and algorithms, precise facial recognition is tough. In predicting the expression of a face, machine learning/artificial intelligence plays a significant role. The deep learning techniques are widely used in more challenging real-world problems which are highly encouraged in facial emotional analysis. In this article, we use three phases for facial expression recognition techniques. The principal component… More >

R. K. Rojin^1,*, M. Mary Linda²

Intelligent Automation & Soft Computing, Vol.33, No.1, pp. 245-258, 2022, DOI:10.32604/iasc.2022.021834 - 05 January 2022

Abstract Microgrids (MG) are distribution networks encompassing distributed energy sources. As it obtains the power from these resources, few problems such as instability along with Steady-State (SS) issues are noticed. To address the stability issues, that arise due to disturbances of low magnitude. Small-Signals Stability (SSS) becomes mandatory in the network. Convergence at local optimum is one of the major issues noticed with the existing optimization algorithms. This paper proposes a detailed model of SSS in Direct Current (DC)-Alternate Current (AC) Hybrid MG (HMG) using Proportional Integral and Derivative Controller (PIDC) tuned with Modified Particle Swarm… More >

R. Saravana Ram^1,*, M. Vinoth Kumar², N. Krishnamoorthy³, A. Baseera⁴, D. Mansoor Hussain⁵, N. Susila⁶

Computer Systems Science and Engineering, Vol.42, No.2, pp. 545-460, 2022, DOI:10.32604/csse.2022.021681 - 04 January 2022

Abstract Major fields such as military applications, medical fields, weather forecasting, and environmental applications use wireless sensor networks for major computing processes. Sensors play a vital role in emerging technologies of the 20th century. Localization of sensors in needed locations is a very serious problem. The environment is home to every living being in the world. The growth of industries after the industrial revolution increased pollution across the environment. Owing to recent uncontrolled growth and development, sensors to measure pollution levels across industries and surroundings are needed. An interesting and challenging task is choosing the place… More >

Sobia Pervaiz¹, Waqas Haider Bangyal², Adnan Ashraf³, Kashif Nisar^4,*, Muhammad Reazul Haque⁵, Ag. Asri Bin Ag. Ibrahim⁴, BS Chowdhry⁶, Waqas Rasheed⁷, Joel J. P. C. Rodrigues^8,9, Richard Etengu⁵, Danda B. Rawat¹⁰

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1427-1444, 2022, DOI:10.32604/iasc.2022.017304 - 09 December 2021

Abstract In existing meta-heuristic algorithms, population initialization forms a huge part towards problem optimization. These calculations can impact variety and combination to locate a productive ideal arrangement. Especially, for perceiving the significance of variety and intermingling, different specialists have attempted to improve the presentation of meta-heuristic algorithms. Particle Swarm Optimization (PSO) algorithm is a populace-based, shrewd stochastic inquiry strategy that is motivated by the inherent honey bee swarm food search mechanism. Population initialization is an indispensable factor in the PSO algorithm. To improve the variety and combination factors, rather than applying the irregular circulation for the… More >

Muhammad Adnan Khan^1,2, Asma Kanwal³, Sagheer Abbas³, Faheem Khan⁴, T. Whangbo^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3607-3619, 2022, DOI:10.32604/cmc.2022.023480 - 07 December 2021

Abstract Cloud computing is providing IT services to its customer based on Service level agreements (SLAs). It is important for cloud service providers to provide reliable Quality of service (QoS) and to maintain SLAs accountability. Cloud service providers need to predict possible service violations before the emergence of an issue to perform remedial actions for it. Cloud users’ major concerns; the factors for service reliability are based on response time, accessibility, availability, and speed. In this paper, we, therefore, experiment with the parallel mutant-Particle swarm optimization (PSO) for the detection and predictions of QoS violations in More >

Supreet Singh^1,2, Nitin Mittal¹, Urvinder Singh², Rohit Salgotra², Atef Zaguia³, Dilbag Singh^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3445-3462, 2022, DOI:10.32604/cmc.2022.023004 - 07 December 2021

Abstract This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm (TSNMRA) which uses hybridization concept of tunicate swarm algorithm (TSA) and naked mole-rat algorithm (NMRA). This newly developed algorithm uses the characteristics of both algorithms (TSA and NMRA) and enhance the exploration abilities of NMRA. Apart from the hybridization concept, important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing mutation operator and there is no need to define its value manually. For evaluating the working capabilities of proposed TSNMRA, it is More >