R. Ganesan^1,*, G. Sankaranarayanan¹, M. Pradeep Kumar², V. K. Bupesh Raja¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 667-681, 2023, DOI:10.32604/iasc.2023.031932

Abstract This research introduces a challenge in integrating and cleaning the data, which is a crucial task in object matching. While the object is detected and then measured, the vibration at different light intensities may influence the durability and reliability of mechanical systems or structures and cause problems such as damage, abnormal stopping, and disaster. Recent research failed to improve the accuracy rate and the computation time in tracking an object and in the vibration measurement. To solve all these problems, this proposed research simplifies the scaling factor determination by assigning a known real-world dimension to a predetermined portion of the… More >

S. Sridevi^*, Jeevaa Katiravan

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 223-233, 2023, DOI:10.32604/iasc.2023.031928

Abstract Scientific workflows have gained the emerging attention in sophisticated large-scale scientific problem-solving environments. The pay-per-use model of cloud, its scalability and dynamic deployment enables it suited for executing scientific workflow applications. Since the cloud is not a utopian environment, failures are inevitable that may result in experiencing fluctuations in the delivered performance. Though a single task failure occurs in workflow based applications, due to its task dependency nature, the reliability of the overall system will be affected drastically. Hence rather than reactive fault-tolerant approaches, proactive measures are vital in scientific workflows. This work puts forth an attempt to concentrate on… More >

Ahmed S. Ghiduk^1,2,*, Abdullah Alharbi¹

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 647-665, 2023, DOI:10.32604/iasc.2023.031865

Abstract Many search-based algorithms have been successfully applied in several software engineering activities. Genetic algorithms (GAs) are the most used in the scientific domains by scholars to solve software testing problems. They imitate the theory of natural selection and evolution. The harmony search algorithm (HSA) is one of the most recent search algorithms in the last years. It imitates the behavior of a musician to find the best harmony. Scholars have estimated the similarities and the differences between genetic algorithms and the harmony search algorithm in diverse research domains. The test data generation process represents a critical task in software validation.… More >

Ch. Venkat Ramana^*, Niranjan Ramchandra Thote, Arun Kumar Singh

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 1205-1214, 2023, DOI:10.32604/iasc.2023.031838

Abstract The tension cracks and joints in rock or soil slopes affect their failure stability. Prediction of rock or soil slope failure is one of the most challenging tasks in the earth sciences. The actual slopes consist of inhomogeneous materials, complex morphology, and erratic joints. Most studies concerning the failure of rock slopes primarily focused on determining Factor of Safety (FoS) and Critical Slip Surface (CSS). In this article, the effect of inclined tension crack on a rock slope failure is studied numerically with Shear Strength Reduction Factor (SRF) method. An inclined Tension Crack (TC) influences the magnitude and location of… More >

S. Harika^1,*, R. Seyezhai¹, A. Jawahar²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 895-910, 2023, DOI:10.32604/iasc.2023.031829

Abstract The solar powered systems require high step-up converter for efficient energy transfer. For this, quasi-impedance network converter has been introduced. The quasi-impedance network converter (QZNC) is of two types: type-1 and type-2 configuration. Both the type-1 and type-2 QZNC configurations have drooping voltage gain profile due to presence of high switching noise. To overcome this, a new quasi-impedance network converter synchronizing the switching circuit with low frequency noise has been proposed. In this paper, the proposed QZNC configuration utilizes the current controlling diode to prevent the output voltage drop. Thus, the suggested topology provides linear high voltage gain profile, low… More >

Rashad A. Al-Jawfi^*

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 957-965, 2023, DOI:10.32604/iasc.2023.031700

Abstract Activation functions play an essential role in converting the output of the artificial neural network into nonlinear results, since without this nonlinearity, the results of the network will be less accurate. Nonlinearity is the mission of all nonlinear functions, except for polynomials. The activation function must be differentiable for backpropagation learning. This study’s objective is to determine the best activation functions for the approximation of each fractal image. Different results have been attained using Matlab and Visual Basic programs, which indicate that the bounded function is more helpful than other functions. The non-linearity of the activation function is important when… More >

N. M. Balamurugan^1,*, K. Maithili², T. K. S. Rathish Babu³, M. Adimoolam⁴

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 499-514, 2023, DOI:10.32604/iasc.2023.031661

Abstract Diabetic Eye Disease (DED) is a fundamental cause of blindness in human beings in the medical world. Different techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy (DR). The Machine Learning (ML) and the Deep Learning (DL) algorithms are the predominant techniques to project and explore the images of DR. Even though some solutions were adapted to challenge the cause of DR disease, still there should be an efficient and accurate DR prediction to be adapted to refine its performance. In this work, a hybrid technique was proposed for classification and prediction of DR. The… More >

Ping-Yueh Chang¹, Fu-I Chou¹, Po-Yuan Yang^2,*, Shao-Hsien Chen³

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 23-38, 2023, DOI:10.32604/iasc.2023.031609

Abstract This paper proposes a hybrid multi-object optimization method integrating a uniform design, an adaptive network-based fuzzy inference system (ANFIS), and a multi-objective particle swarm optimizer (MOPSO) to optimize the rigid tapping parameters and minimize the synchronization errors and cycle times of computer numerical control (CNC) machines. First, rigid tapping parameters and uniform (including 41-level and 19-level) layouts were adopted to collect representative data for modeling. Next, ANFIS was used to build the model for the collected 41-level and 19-level uniform layout experiment data. In tapping center machines, the synchronization errors and cycle times are important considerations, so these two objects… More >

S. Kalavathi^1,*, R. Nedunchelian²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 39-56, 2023, DOI:10.32604/iasc.2023.031522

Abstract Network analysis is a promising field in the area of network applications as different types of traffic grow enormously and exponentially. Reliable route prediction is a challenging task in the Large Scale Networks (LSN). Various non-self-learning and self-learning approaches have been adopted to predict reliable routing. Routing protocols decide how to send all the packets from source to the destination addresses across the network through their IP. In the current era, dynamic protocols are preferred as they network self-learning internally using an algorithm and may not entail being updated physically more than the static protocols. A novel method named Reliable… More >

S. Samsudeen Shaffi^1,*, I. Muthulakshmi²

Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 183-192, 2023, DOI:10.32604/iasc.2023.031494

Abstract As data grows in size, search engines face new challenges in extracting more relevant content for users’ searches. As a result, a number of retrieval and ranking algorithms have been employed to ensure that the results are relevant to the user’s requirements. Unfortunately, most existing indexes and ranking algorithms crawl documents and web pages based on a limited set of criteria designed to meet user expectations, making it impossible to deliver exceptionally accurate results. As a result, this study investigates and analyses how search engines work, as well as the elements that contribute to higher ranks. This paper addresses the… More >