Table of Content
- Vol.48, No.1, 2024
- Vol.48, No.2, 2024
- Vol.48, No.3, 2024
- Vol.48, No.4, 2024
- Vol.48, No.5, 2024
- Vol.48, No.6, 2024
- Vol.44, No.1, 2023
- Vol.44, No.2, 2023
- Vol.44, No.3, 2023
- Vol.45, No.1, 2023
- Vol.45, No.2, 2023
- Vol.45, No.3, 2023
- Vol.46, No.1, 2023
- Vol.46, No.2, 2023
- Vol.46, No.3, 2023
- Vol.47, No.1, 2023
- Vol.47, No.2, 2023
- Vol.47, No.3, 2023
- Vol.40, No.1, 2022
- Vol.40, No.2, 2022
- Vol.40, No.3, 2022
- Vol.41, No.1, 2022
- Vol.41, No.2, 2022
- Vol.41, No.3, 2022
- Vol.42, No.1, 2022
- Vol.42, No.2, 2022
- Vol.42, No.3, 2022
- Vol.43, No.1, 2022
- Vol.43, No.2, 2022
- Vol.43, No.3, 2022
- Vol.36, No.1, 2021
- Vol.36, No.2, 2021
- Vol.36, No.3, 2021
- Vol.37, No.1, 2021
- Vol.37, No.2, 2021
- Vol.37, No.3, 2021
- Vol.38, No.1, 2021
- Vol.38, No.2, 2021
- Vol.38, No.3, 2021
- Vol.39, No.1, 2021
- Vol.39, No.2, 2021
- Vol.39, No.3, 2021
- Vol.35, No.1, 2020
- Vol.35, No.2, 2020
- Vol.35, No.3, 2020
- Vol.35, No.4, 2020
- Vol.35, No.5, 2020
- Vol.35, No.6, 2020
- Vol.34, No.1, 2019
- Vol.34, No.2, 2019
- Vol.34, No.3, 2019
- Vol.34, No.4, 2019
- Vol.34, No.5, 2019
- Vol.34, No.6, 2019
- Vol.33, No.1, 2018
- Vol.33, No.2, 2018
- Vol.33, No.3, 2018
- Vol.33, No.4, 2018
- Vol.33, No.5, 2018
- Vol.33, No.6, 2018
About the Journal
The Computer Systems Science and Engineering journal is devoted to the publication of high quality papers on theoretical developments in computer systems science, and their applications in computer systems engineering. Original research papers, state-of-the-art reviews and technical notes are invited for publication.
Indexing and Abstracting
EBSCO, OpenAIRE, OpenALEX, CNKI Scholar, PubScholar, Portico, etc.
Starting from January 2025, Computer Systems Science and Engineering will transition to a continuous publication model, and accepted articles will be promptly published online upon completion of the peer review and production processes.
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Open Access
ARTICLE
Enhancing Vehicle Overtaking System via LoRa-Enabled Vehicular Communication Approach
Computer Systems Science and Engineering, Vol.49, pp. 239-258, 2025, DOI:10.32604/csse.2024.056582 - 10 January 2025
Abstract Vehicle overtaking poses significant risks and leads to injuries and losses on Malaysia’s roads. In most scenarios, insufficient and untimely information available to drivers for accessing road conditions and their surrounding environment is the primary factor that causes these incidents. To address these issues, a comprehensive system is required to provide real-time assistance to drivers. Building upon our previous research on a LoRa-based lane change decision-aid system, this study proposes an enhanced Vehicle Overtaking System (VOS). This system utilizes long-range (LoRa) communication for reliable real-time data exchange between vehicles (V2V) and the cloud (V2C). By More >
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Open Access
ARTICLE
3D Reconstruction for Early Detection of Liver Cancer
Computer Systems Science and Engineering, Vol.49, pp. 213-238, 2025, DOI:10.32604/csse.2024.059491 - 10 January 2025
Abstract Globally, liver cancer ranks as the sixth most frequent malignancy cancer. The importance of early detection is undeniable, as liver cancer is the fifth most common disease in men and the ninth most common cancer in women. Recent advances in imaging, biomarker discovery, and genetic profiling have greatly enhanced the ability to diagnose liver cancer. Early identification is vital since liver cancer is often asymptomatic, making diagnosis difficult. Imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT), and ultrasonography can be used to identify liver cancer once a sample of liver tissue is… More >
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Open Access
ARTICLE
Energy-Efficient Internet of Things-Based Wireless Sensor Network for Autonomous Data Validation for Environmental Monitoring
Computer Systems Science and Engineering, Vol.49, pp. 185-212, 2025, DOI:10.32604/csse.2024.056535 - 10 January 2025
Abstract This study presents an energy-efficient Internet of Things (IoT)-based wireless sensor network (WSN) framework for autonomous data validation in remote environmental monitoring. We address two critical challenges in WSNs: ensuring data reliability and optimizing energy consumption. Our novel approach integrates an artificial neural network (ANN)-based multi-fault detection algorithm with an energy-efficient IoT-WSN architecture. The proposed ANN model is designed to simultaneously detect multiple fault types, including spike faults, stuck-at faults, outliers, and out-of-range faults. We collected sensor data at 5-minute intervals over three months, using temperature and humidity sensors. The ANN was trained on 70%… More >
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Open Access
ARTICLE
XGBoost Based Multiclass NLOS Channels Identification in UWB Indoor Positioning System
Computer Systems Science and Engineering, Vol.49, pp. 159-183, 2025, DOI:10.32604/csse.2024.058741 - 03 January 2025
Abstract Accurate non-line of sight (NLOS) identification technique in ultra-wideband (UWB) location-based services is critical for applications like drone communication and autonomous navigation. However, current methods using binary classification (LOS/NLOS) oversimplify real-world complexities, with limited generalisation and adaptability to varying indoor environments, thereby reducing the accuracy of positioning. This study proposes an extreme gradient boosting (XGBoost) model to identify multi-class NLOS conditions. We optimise the model using grid search and genetic algorithms. Initially, the grid search approach is used to identify the most favourable values for integer hyperparameters. In order to achieve an optimised model configuration,… More >
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Open Access
REVIEW
Navigating the Complexities of Controller Placement in SD-WANs: A Multi-Objective Perspective on Current Trends and Future Challenges
Computer Systems Science and Engineering, Vol.49, pp. 123-157, 2025, DOI:10.32604/csse.2024.058314 - 03 January 2025
Abstract This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placement Problem (CPP). As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management, the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge. This review delves into recent innovations in multi-objective controller placement strategies, including clustering techniques, heuristic-based approaches, and the integration of machine learning and deep learning models. Each methodology is critically More >
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Open Access
ARTICLE
Revolutionizing Automotive Security: Connected Vehicle Security Blockchain Solutions for Enhancing Physical Flow in the Automotive Supply Chain
Computer Systems Science and Engineering, Vol.49, pp. 99-122, 2025, DOI:10.32604/csse.2024.057754 - 03 January 2025
（This article belongs to the Special Issue: Blockchain, Artificial Intelligence, Internet of Things and 6G Convergence)
Abstract The rapid growth of the automotive industry has raised significant concerns about the security of connected vehicles and their integrated supply chains, which are increasingly vulnerable to advanced cyber threats. Traditional authentication methods have proven insufficient, exposing systems to risks such as Sybil, Denial of Service (DoS), and Eclipse attacks. This study critically examines the limitations of current security protocols, focusing on authentication and data exchange vulnerabilities, and explores blockchain technology as a potential solution. Blockchain’s decentralized and cryptographically secure framework can significantly enhance Vehicle-to-Vehicle (V2V) communication, ensure data integrity, and enable transparent, immutable transactions More >
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Open Access
ARTICLE
A Secure Authentication Indexed Choice-Based Graphical Password Scheme for Web Applications and ATMs
Computer Systems Science and Engineering, Vol.49, pp. 79-98, 2025, DOI:10.32604/csse.2024.057439 - 03 January 2025
Abstract Authentication is the most crucial aspect of security and a predominant measure employed in cybersecurity. Cloud computing provides a shared electronic device resource for users via the internet, and the authentication techniques used must protect data from attacks. Previous approaches failed to resolve the challenge of making passwords secure, memorable, usable, and time-saving. Graphical Password (GP) is still not widely utilized in reality because consumers suffer from multiple login stages. This paper proposes an Indexed Choice-Based Graphical Password (ICGP) scheme for improving the authentication part. ICGP consists of two stages: registration and authentication. At the… More >
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Open Access
ARTICLE
Prairie Araneida Optimization Based Fused CNN Model for Intrusion Detection
Computer Systems Science and Engineering, Vol.49, pp. 49-77, 2025, DOI:10.32604/csse.2024.057702 - 03 January 2025
（This article belongs to the Special Issue: Artificial Intelligence for Cyber Security)
Abstract Intrusion detection (ID) is a cyber security practice that encompasses the process of monitoring network activities to identify unauthorized or malicious actions. This includes problems like the difficulties of existing intrusion detection models to identify emerging attacks, generating many false alarms, and their inability and difficulty to adapt themselves with time when it comes to threats, hence to overcome all those existing challenges in this research develop a Prairie Araneida optimization based fused Convolutional Neural Network model (PAO-CNN) for intrusion detection. The fused CNN (Convolutional Neural Netowrk) is a remarkable development since it combines statistical… More >
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Open Access
ARTICLE
An Intelligent Security Service Optimization Method Based on Knowledge Base
Computer Systems Science and Engineering, Vol.49, pp. 19-48, 2025, DOI:10.32604/csse.2024.058327 - 03 January 2025
（This article belongs to the Special Issue: Artificial Intelligence for Cyber Security)
Abstract The network security knowledge base standardizes and integrates network security data, providing a reliable foundation for real-time network security protection solutions. However, current research on network security knowledge bases mainly focuses on their construction, while the potential to optimize intelligent security services for real-time network security protection requires further exploration. Therefore, how to effectively utilize the vast amount of historical knowledge in the field of network security and establish a feedback mechanism to update it in real time, thereby enhancing the detection capability of security services against malicious traffic, has become an important issue. Our… More >
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Open Access
ARTICLE
Automation of Software Development Stages with the OpenAI API
Computer Systems Science and Engineering, Vol.49, pp. 1-17, 2025, DOI:10.32604/csse.2024.056979 - 03 January 2025
Abstract In recent years, automation has become a key focus in software development as organizations seek to improve efficiency and reduce time-to-market. The integration of artificial intelligence (AI) tools, particularly those using natural language processing (NLP) like ChatGPT, has opened new possibilities for automating various stages of the development lifecycle. The primary objective of this study is to evaluate the effectiveness of ChatGPT in automating various phases of software development. An artificial intelligence (AI) tool was developed using the OpenAI—Application Programming Interface (API), incorporating two key functionalities: 1) generating user stories based on case or process… More >
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Open Access
REVIEW
Navigating the Complexities of Controller Placement in SD-WANs: A Multi-Objective Perspective on Current Trends and Future Challenges
Computer Systems Science and Engineering, Vol.49, pp. 123-157, 2025, DOI:10.32604/csse.2024.058314
Abstract This review article provides a comprehensive analysis of the latest advancements and persistent challenges in Software-Defined Wide Area Networks (SD-WANs), with a particular emphasis on the multi-objective Controller Placement Problem (CPP). As SD-WAN technology continues to gain prominence for its capacity to offer flexible and efficient network management, the task of 36optimally placing controllers—responsible for orchestrating and managing network traffic—remains a critical yet complex challenge. This review delves into recent innovations in multi-objective controller placement strategies, including clustering techniques, heuristic-based approaches, and the integration of machine learning and deep learning models. Each methodology is critically More >
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Open Access
ARTICLE
Learning-Based Metaheuristic Approach for Home Healthcare Optimization Problem
Computer Systems Science and Engineering, Vol.45, No.1, pp. 1-19, 2023, DOI:10.32604/csse.2023.029058
Abstract This research focuses on the home health care optimization problem that involves staff routing and scheduling problems. The considered problem is an extension of multiple travelling salesman problem. It consists of finding the shortest path for a set of caregivers visiting a set of patients at their homes in order to perform various tasks during a given horizon. Thus, a mixed-integer linear programming model is proposed to minimize the overall service time performed by all caregivers while respecting the workload balancing constraint. Nevertheless, when the time horizon become large, practical-sized instances become very difficult to More >
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Open Access
ARTICLE
Reinforcement Learning with an Ensemble of Binary Action Deep Q-Networks
Computer Systems Science and Engineering, Vol.46, No.3, pp. 2651-2666, 2023, DOI:10.32604/csse.2023.031720
Abstract With the advent of Reinforcement Learning (RL) and its continuous
progress, state-of-the-art RL systems have come up for many challenging and
real-world tasks. Given the scope of this area, various techniques are found in
the literature. One such notable technique, Multiple Deep Q-Network (DQN) based
RL systems use multiple DQN-based-entities, which learn together and communicate with each other. The learning has to be distributed wisely among all entities in
such a scheme and the inter-entity communication protocol has to be carefully
designed. As more complex DQNs come to the fore, the overall complexity of these… More >
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Open Access
ARTICLE
TC-Net: A Modest & Lightweight Emotion Recognition System Using Temporal Convolution Network
Computer Systems Science and Engineering, Vol.46, No.3, pp. 3355-3369, 2023, DOI:10.32604/csse.2023.037373
Abstract Speech signals play an essential role in communication and provide an efficient way to exchange information between humans and machines. Speech Emotion Recognition (SER) is one of the critical sources for human evaluation, which is applicable in many real-world applications such as healthcare, call centers, robotics, safety, and virtual reality. This work developed a novel TCN-based emotion recognition system using speech signals through a spatial-temporal convolution network to recognize the speaker’s emotional state. The authors designed a Temporal Convolutional Network (TCN) core block to recognize long-term dependencies in speech signals and then feed these temporal More >
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Open Access
ARTICLE
Big Data Analytics with Optimal Deep Learning Model for Medical Image Classification
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1433-1449, 2023, DOI:10.32604/csse.2023.025594
Abstract In recent years, huge volumes of healthcare data are getting generated in various forms. The advancements made in medical imaging are tremendous owing to which biomedical image acquisition has become easier and quicker. Due to such massive generation of big data, the utilization of new methods based on Big Data Analytics (BDA), Machine Learning (ML), and Artificial Intelligence (AI) have become essential. In this aspect, the current research work develops a new Big Data Analytics with Cat Swarm Optimization based deep Learning (BDA-CSODL) technique for medical image classification on Apache Spark environment. The aim of… More >
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Open Access
ARTICLE
Deep-BERT: Transfer Learning for Classifying Multilingual Offensive Texts on Social Media
Computer Systems Science and Engineering, Vol.44, No.2, pp. 1775-1791, 2023, DOI:10.32604/csse.2023.027841
Abstract Offensive messages on social media, have recently been frequently used to harass and criticize people. In recent studies, many promising algorithms have been developed to identify offensive texts. Most algorithms analyze text in a unidirectional manner, where a bidirectional method can maximize performance results and capture semantic and contextual information in sentences. In addition, there are many separate models for identifying offensive texts based on monolingual and multilingual, but there are a few models that can detect both monolingual and multilingual-based offensive texts. In this study, a detection system has been developed for both monolingual… More >
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Open Access
ARTICLE
Future Event Prediction Based on Temporal Knowledge Graph Embedding
Computer Systems Science and Engineering, Vol.44, No.3, pp. 2411-2423, 2023, DOI:10.32604/csse.2023.026823
Abstract Accurate prediction of future events brings great benefits and reduces losses for society in many domains, such as civil unrest, pandemics, and crimes. Knowledge graph is a general language for describing and modeling complex systems. Different types of events continually occur, which are often related to historical and concurrent events. In this paper, we formalize the future event prediction as a temporal knowledge graph reasoning problem. Most existing studies either conduct reasoning on static knowledge graphs or assume knowledges graphs of all timestamps are available during the training process. As a result, they cannot effectively… More >
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Open Access
ARTICLE
Intelligent Deep Learning Enabled Human Activity Recognition for Improved Medical Services
Computer Systems Science and Engineering, Vol.44, No.2, pp. 961-977, 2023, DOI:10.32604/csse.2023.024612
Abstract Human Activity Recognition (HAR) has been made simple in recent years, thanks to recent advancements made in Artificial Intelligence (AI) techniques. These techniques are applied in several areas like security, surveillance, healthcare, human-robot interaction, and entertainment. Since wearable sensor-based HAR system includes in-built sensors, human activities can be categorized based on sensor values. Further, it can also be employed in other applications such as gait diagnosis, observation of children/adult’s cognitive nature, stroke-patient hospital direction, Epilepsy and Parkinson’s disease examination, etc. Recently-developed Artificial Intelligence (AI) techniques, especially Deep Learning (DL) models can be deployed to accomplish… More >
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Open Access
ARTICLE
Computer Vision and Deep Learning-enabled Weed Detection Model for Precision Agriculture
Computer Systems Science and Engineering, Vol.44, No.3, pp. 2759-2774, 2023, DOI:10.32604/csse.2023.027647
Abstract Presently, precision agriculture processes like plant disease, crop yield prediction, species recognition, weed detection, and irrigation can be accomplished by the use of computer vision (CV) approaches. Weed plays a vital role in influencing crop productivity. The wastage and pollution of farmland's natural atmosphere instigated by full coverage chemical herbicide spraying are increased. Since the proper identification of weeds from crops helps to reduce the usage of herbicide and improve productivity, this study presents a novel computer vision and deep learning based weed detection and classification (CVDL-WDC) model for precision agriculture. The proposed CVDL-WDC technique More >
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Open Access
ARTICLE
Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks
Computer Systems Science and Engineering, Vol.44, No.1, pp. 1-17, 2023, DOI:10.32604/csse.2023.024973
Abstract In recent times, real time wireless networks have found their applicability in several practical applications such as smart city, healthcare, surveillance, environmental monitoring, etc. At the same time, proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks. This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed IM-EECNL technique involves two major processes namely node localization and clustering. Firstly, Chaotic Water Strider Algorithm based Node Localization (CWSANL) technique to determine the unknown position of the nodes. More >
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Open Access
ARTICLE
Prediction Model for Coronavirus Pandemic Using Deep Learning
Computer Systems Science and Engineering, Vol.40, No.3, pp. 947-961, 2022, DOI:10.32604/csse.2022.019288
Abstract The recent global outbreak of COVID-19 damaged the world health systems, human health, economy, and daily life badly. None of the countries was ready to face this emerging health challenge. Health professionals were not able to predict its rise and next move, as well as the future curve and impact on lives in case of a similar pandemic situation happened. This created huge chaos globally, for longer and the world is still struggling to come up with any suitable solution. Here the better use of advanced technologies, such as artificial intelligence and deep learning, may… More >
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Open Access
ARTICLE
Interactive Middleware Services for Heterogeneous Systems
Computer Systems Science and Engineering, Vol.41, No.3, pp. 1241-1253, 2022, DOI:10.32604/csse.2022.021997
Abstract Computing has become more invisible, widespread and ubiquitous since the inception of the Internet of Things (IoT) and Web of Things. Multiple devices that surround us meet user’s requirements everywhere. Multiple Middleware Framework (MF) designs have come into existence because of the rapid development of interactive services in Heterogeneous Systems. This resulted in the delivery of interactive services throughout Heterogeneous Environments (HE). Users are given free navigation between devices in a widespread environment and continuously interact with each other from any chosen device. Numerous interactive devices with recent interactive platforms (for example, Smart Phones, Mobile… More >
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Open Access
ARTICLE
A Novel Post-Quantum Blind Signature for Log System in Blockchain
Computer Systems Science and Engineering, Vol.41, No.3, pp. 945-958, 2022, DOI:10.32604/csse.2022.022100
Abstract In recent decades, log system management has been widely studied for data security management. System abnormalities or illegal operations can be found in time by analyzing the log and provide evidence for intrusions. In order to ensure the integrity of the log in the current system, many researchers have designed it based on blockchain. However, the emerging blockchain is facing significant security challenges with the increment of quantum computers. An attacker equipped with a quantum computer can extract the user's private key from the public key to generate a forged signature, destroy the structure of… More >
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Open Access
REVIEW
Intrusion Detection Systems Using Blockchain Technology: A Review, Issues and Challenges
Computer Systems Science and Engineering, Vol.40, No.1, pp. 87-112, 2022, DOI:10.32604/csse.2022.017941
（This article belongs to the Special Issue: Emerging Trends in Intelligent Communication and Wireless Technologies)
Abstract Intrusion detection systems that have emerged in recent decades can identify a variety of malicious attacks that target networks by employing several detection approaches. However, the current approaches have challenges in detecting intrusions, which may affect the performance of the overall detection system as well as network performance. For the time being, one of the most important creative technological advancements that plays a significant role in the professional world today is blockchain technology. Blockchain technology moves in the direction of persistent revolution and change. It is a chain of blocks that covers information and maintains… More >
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Open Access
ARTICLE
A New Random Forest Applied to Heavy Metal Risk Assessment
Computer Systems Science and Engineering, Vol.40, No.1, pp. 207-221, 2022, DOI:10.32604/csse.2022.018301
Abstract As soil heavy metal pollution is increasing year by year, the risk assessment of soil heavy metal pollution is gradually gaining attention. Soil heavy metal datasets are usually imbalanced datasets in which most of the samples are safe samples that are not contaminated with heavy metals. Random Forest (RF) has strong generalization ability and is not easy to overfit. In this paper, we improve the Bagging algorithm and simple voting method of RF. A W-RF algorithm based on adaptive Bagging and weighted voting is proposed to improve the classification performance of RF on imbalanced datasets.… More >
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Open Access
ARTICLE
Smart Mina: LoRaWAN Technology for Smart Fire Detection Application for Hajj Pilgrimage
Computer Systems Science and Engineering, Vol.40, No.1, pp. 259-272, 2022, DOI:10.32604/csse.2022.018458
Abstract The Long-Range Wide Area Network (LoRaWAN) is one of the used communication systems that serve and enables the deployment of the Internet of Things (IoT), which occasionally transmit small size data. As part of the Low Power Wide Area Network (LPWAN), LoRaWAN is characterized by its ability for low power consumption. In addition, it is built to provide more extended coverage and higher capacity with minimum cost. In this paper, we investigate the feasibility and scalability of LoRaWAN for the Mina area using a realistic network model. Mina, known as the world’s largest tent city,… More >
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Open Access
ARTICLE
An Approximate Numerical Methods for Mathematical and Physical Studies for Covid-19 Models
Computer Systems Science and Engineering, Vol.42, No.3, pp. 1147-1163, 2022, DOI:10.32604/csse.2022.020869
（This article belongs to the Special Issue: Advances in Computational Intelligence and its Applications)
Abstract The advancement in numerical models of serious resistant illnesses is a key research territory in different fields including the nature and the study of disease transmission. One of the aims of these models is to comprehend the elements of conduction of these infections. For the new strain of Covid-19 (Coronavirus), there has been no immunization to protect individuals from the virus and to forestall its spread so far. All things being equal, control procedures related to medical services, for example, social distancing or separation, isolation, and travel limitations can be adjusted to control this pandemic.… More >
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Open Access
ARTICLE
Fuzzy Based Ant Colony Optimization Scheduling in Cloud Computing
Computer Systems Science and Engineering, Vol.40, No.2, pp. 581-592, 2022, DOI:10.32604/csse.2022.019175
Abstract Cloud computing is an Information Technology deployment model established on virtualization. Task scheduling states the set of rules for task allocations to an exact virtual machine in the cloud computing environment. However, task scheduling challenges such as optimal task scheduling performance solutions, are addressed in cloud computing. First, the cloud computing performance due to task scheduling is improved by proposing a Dynamic Weighted Round-Robin algorithm. This recommended DWRR algorithm improves the task scheduling performance by considering resource competencies, task priorities, and length. Second, a heuristic algorithm called Hybrid Particle Swarm Parallel Ant Colony Optimization is More >
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Open Access
ARTICLE
Software Reliability Assessment Using Hybrid Neuro-Fuzzy Model
Computer Systems Science and Engineering, Vol.41, No.3, pp. 891-902, 2022, DOI:10.32604/csse.2022.019943
Abstract Software reliability is the primary concern of software development organizations, and the exponentially increasing demand for reliable software requires modeling techniques to be developed in the present era. Small unnoticeable drifts in the software can culminate into a disaster. Early removal of these errors helps the organization improve and enhance the software’s reliability and save money, time, and effort. Many soft computing techniques are available to get solutions for critical problems but selecting the appropriate technique is a big challenge. This paper proposed an efficient algorithm that can be used for the prediction of software… More >
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Open Access
ARTICLE
Optimizing Traffic Signals in Smart Cities Based on Genetic Algorithm
Computer Systems Science and Engineering, Vol.40, No.1, pp. 65-74, 2022, DOI:10.32604/csse.2022.016730
Abstract Current traffic signals in Jordan suffer from severe congestion due to many factors, such as the considerable increase in the number of vehicles and the use of fixed timers, which still control existing traffic signals. This condition affects travel demand on the streets of Jordan. This study aims to improve an intelligent road traffic management system (IRTMS) derived from the human community-based genetic algorithm (HCBGA) to mitigate traffic signal congestion in Amman, Jordan’s capital city. The parameters considered for IRTMS are total time and waiting time, and fixed timers are still used for control. By More >
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