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Journal articles on the topic 'Money Particle Swarm Optimization'

Author: Grafiati

Published: 7 June 2025

Last updated: 2 August 2025

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1

Guo, Aifang, Lina Zhu, and Lingjie Chang. "An Optimization Method for Enterprise Resource Integration Based on Improved Particle Swarm Optimization." Computational Intelligence and Neuroscience 2022 (May 31, 2022): 1–10. http://dx.doi.org/10.1155/2022/6928989.

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An enterprise’s development and growth are inextricably linked to rational and efficient resource integration and optimization. This study focuses on the reorganization and integration of industrial elements inside the firm from the standpoint of resource integration. The ideal resource integration strategy is investigated by integrating the industrial parts of a certain enterprise in order to increase the efficiency of project completion and lower enterprise expenses. The enterprise’s internal material and human resources are limited, but it is frequently necessary to execute numerous activit

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Tang, Longjiao. "Logistics Path Planning based on Improved Particle Swarm Optimization Algorithm." Scalable Computing: Practice and Experience 26, no. 3 (2025): 1276–83. https://doi.org/10.12694/scpe.v26i3.4205.

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In order to solve the problem of vehicle path scheduling management more reasonably, the author proposes a logistics path planning research based on improved particle swarm optimization algorithm. The author introduces a particle swarm optimization algorithm that incorporates a dynamic monkey jumping mechanism. Initially, dynamic population grouping is used to assign varying dynamic inertia weights, enhancing the algorithm’s speed. Subsequently, the monkey jumping mechanism is added to ensure global convergence. This enhanced algorithm was then tested on two logistics distribution path optimiz

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Merlina, Nita, Ade Chandra, and Nissa Almira Mayangky. "PENERAPAN PSO UNTUK SENTIMEN ANALISIS PADA REVIEW MATA UANG KRIPTO MENGGUNAKAN METODE NAÏVE BAYES." INTI Nusa Mandiri 18, no. 2 (2024): 115–21. http://dx.doi.org/10.33480/inti.v18i2.4982.

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In the digital age emerging currencies using digital technology called currency crypto money. Many people use cryptocurrencies to invest. This triggered the sentiment in society on social media twitter, there are positive opinions and there are negative opinions. The purpose of this study is to determine the public sentiment regarding the review of crypto currency and then classify it into two sentiments, namely positive and negative sentiments. The classifier method used is Naïve Bayes, Naïve Bayes is a good classifier method but has shortcomings in the selection of features therefore Particl

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Venkataiah, V., M. Nagaratna, and Ramakanta Mohanty. "Application of Chaotic Increasing Linear Inertia Weight and Diversity Improved Particle Swarm Optimization to Predict Accurate Software Cost Estimation." International Journal of Electrical and Electronics Research 10, no. 2 (2022): 154–60. http://dx.doi.org/10.37391/ijeer.100218.

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Nowadays usage of software products is increases exponential in different areas in society, accordingly, the development of software products as well increases by the software organizations, but they are unable to focus to predict effective techniques for planning resources, reliable design, and estimation of time, budget, and high quality at the preliminary phase of the development of the product lifecycle. Consequently, it delivered improper software products. Hence, a customer loses the money, time, and not belief on the company as well as effort of teamwork will be lost. We need an efficie

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Yusuf, Priyo Anggodo, and Firdaus Mahmudy Wayan. "A Novel Forecasting Based on Automatic-optimized Fuzzy Time Series." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 4 (2018): 1809–17. https://doi.org/10.12928/TELKOMNIKA.v16i4.8430.

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In this paper, we propose a new method for forecasting based on automatic-optimized fuzzy time series to forecast Indonesia Inflation Rate (IIR). First, we propose the forecasting model of two-factor highorder fuzzy-trend logical relationships groups (THFLGs) for predicting the IIR. Second, we propose the interval optimization using automatic clustering and particle swarm optimization (ACPSO) to optimize the interval of main factor IIR and secondary factor SF, where SF = {Customer Price Index (CPI), the Bank of Indonesia (BI) Rate, Rupiah Indonesia /US Dollar (IDR/USD) Exchange rate, Money Sup

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Tatale, Subhash, and Vudatha Chandra Prakash. "Automatic Generation and Optimization of Combinatorial Test Cases from UML Activity Diagram Using Particle Swarm Optimization." Ingénierie des systèmes d information 27, no. 1 (2022): 49–59. http://dx.doi.org/10.18280/isi.270106.

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Generation of test cases is one of the essential activities of the software testing process. The process of executing a programme to identify defects to improve the system's quality is known as software testing. Manually writing test cases takes time, effort, and money. On the other hand, generating test cases automatically is the solution to this problem. For this automation process, a model-based test case generation technique would be acceptable. A model is usually required to generate test cases in the model-based testing technique. Nowadays, researchers have relied on the activity diagram

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Rohmayani, Dini. "ANALYSIS OF STUDENT TUITION FEE PAY DELAY PREDICTION USING NAIVE BAYES ALGORITHM WITH PARTICLE SWARM OPTIMATION OPTIMAZATION (CASE STUDY : POLITEKNIK TEDC BANDUNG)." Jurnal Teknologi Informasi dan Pendidikan 13, no. 2 (2020): 1–8. http://dx.doi.org/10.24036/tip.v13i2.317.

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One source of funds that plays a very important role in education or teaching and learning activities is the Donation of Education Development or tuition fee. The problem faced by TEDC Polytechnic of Bandung is based on historical data from the financial department there are still many students who are late in making tuition payments, for that the authors make an analysis in predicting late payment of fees by using the Naive Bayes algorithm which is compared with Particle Swarm Optimization (PSO) with the purpose of determining the classification pattern is right or late and to find out what i

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Jalaee, Sayyed Abdolmajid, Alireza Shakibaei, Hamid Reza Horry, et al. "A new hybrid metaheuristic method based on biogeography-based optimization and particle swarm optimization algorithm to estimate money demand in Iran." MethodsX 8 (2021): 101226. http://dx.doi.org/10.1016/j.mex.2021.101226.

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Omran, Sherin M., Wessam H. El-Behaidy, and Aliaa A. A. Youssif. "Optimization of Cryptocurrency Algorithmic Trading Strategies Using the Decomposition Approach." Big Data and Cognitive Computing 7, no. 4 (2023): 174. http://dx.doi.org/10.3390/bdcc7040174.

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A cryptocurrency is a non-centralized form of money that facilitates financial transactions using cryptographic processes. It can be thought of as a virtual currency or a payment mechanism for sending and receiving money online. Cryptocurrencies have gained wide market acceptance and rapid development during the past few years. Due to the volatile nature of the crypto-market, cryptocurrency trading involves a high level of risk. In this paper, a new normalized decomposition-based, multi-objective particle swarm optimization (N-MOPSO/D) algorithm is presented for cryptocurrency algorithmic trad

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Xie, Wangsong. "Interbank Offered Rate Based on Artificial Intelligence Algorithm." Mathematical Problems in Engineering 2021 (May 17, 2021): 1–11. http://dx.doi.org/10.1155/2021/9931539.

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Interbank offer rate is the interest rate at which banks lend money to each other in the money market. As a market-oriented core interest rate, Shibor can accurately and timely reflect the capital supply and demand relationship in the money market, and its changes will quickly transmit and affect China’s financial market. Therefore, the purpose of this paper is to predict and study the fluctuation and trend of Shibor. In this paper, the overnight varieties of Shibor were studied and predicted from two time dimensions, namely, daily fluctuation and monthly trend. In the prediction of overnight

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Sadiq, Sheren, and Adel Sabry Eesa. "OPTIMIZATION ALGORITHMS FOR INTRUSION DETECTION SYSTEM: A REVIEW." International Journal of Research -GRANTHAALAYAH 8, no. 8 (2020): 217–25. http://dx.doi.org/10.29121/granthaalayah.v8.i8.2020.1031.

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With the growth and development of the Internet, the devices and the hosts connected to the Internet have become the target for attackers and intruders. Consequently, the integrity of systems and data has become more sophisticated. Meanwhile, many institutions suffer from money-losing or other losses due to attacks on computer systems. Accordingly, the detection of intrusion and attacks has become a challenge and a vital necessity at the same time. Many different methods were used to build intrusion detection systems (IDSs), and all these methods seek to a plus the efficiency of intrusion dete

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Yang, Cheng-Hong, Borcy Lee, and Yu-Da Lin. "Effect of Money Supply, Population, and Rent on Real Estate: A Clustering Analysis in Taiwan." Mathematics 10, no. 7 (2022): 1155. http://dx.doi.org/10.3390/math10071155.

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Real estate is a complex and unpredictable industry because of the many factors that influence it, and conducting a thorough analysis of these factors is challenging. This study explores why house prices have continued to increase over the last 10 years in Taiwan. A clustering analysis based on a double-bottom map particle swarm optimization algorithm was applied to cluster real estate–related data collected from public websites. We report key findings from the clustering results and identify three essential variables that could affect trends in real estate prices: money supply, population, an

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Hardoni, Andre, Dian Palupi Rini, and Sukemi Sukemi. "Integrasi SMOTE pada Naive Bayes dan Logistic Regression Berbasis Particle Swarm Optimization untuk Prediksi Cacat Perangkat Lunak." JURNAL MEDIA INFORMATIKA BUDIDARMA 5, no. 1 (2021): 233. http://dx.doi.org/10.30865/mib.v5i1.2616.

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Software defects are one of the main contributors to information technology waste and lead to rework, thus consuming a lot of time and money. Software defect prediction has the objective of defect prevention by classifying certain modules as defective or not defective. Many researchers have conducted research in the field of software defect prediction using NASA MDP public datasets, but these datasets still have shortcomings such as class imbalance and noise attribute. The class imbalance problem can be overcome by utilizing SMOTE (Synthetic Minority Over-sampling Technique) and the noise attr

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Pelaez-Diaz, Guillermo Napoleón, Rosa Vílchez-Vásquez, Antonio Huaman-Osorio, et al. "Detection of Fungal Infections in Gloriosa Superba Plant Using the Convolution Neural Network Model." Journal of Food Quality 2022 (July 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/7413983.

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Herbal treatments’ efficacy, safety, and mild side effects are also high priorities in primary care. Furthermore, as the world’s population expands, food production becomes more difficult. We need to use innovative biotechnology-based fertilization technologies to boost food production output. Gloriosa superba is one of the most well-known plants for its antibacterial and medicinal capabilities. The money plant is also known as the Gloriosa superba. We used a deep learning-based convolution neural network (CNN) classifier model to optimize the CNN algorithm parameter for better prediction. The

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Martono, Aris, Padeli Padeli, Muhamad Iip Suhaepi, Sugeng Santoso, and Endang Sunandar. "Credit Risk Prediction Model Using Support Vector Machine with Parameter Optimization in Banks." Journal Sensi 10, no. 2 (2024): 124–33. https://doi.org/10.33050/sensi.v10i2.3463.

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Abstract This research aims to determine the Support Vector Machine (SVM) model with Parameter Optimization in predicting loan worthiness to avoid the risk of bad credit at the Bank. Every bank tries to market financial loan products with very strict requirements. One of the requirements is that the company's financial reports must be healthy if it borrows money from a bank to develop the company's business. In the credit analysis process, there are 19 financial factors that must be measured from dozens or even hundreds of companies proposing financial loans, making it difficult for credit ana

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Kebriyaii, Omid, Ali Heidari, Mohammad Khalilzadeh, Jurgita Antucheviciene, and Miroslavas Pavlovskis. "Application of Three Metaheuristic Algorithms to Time-Cost-Quality Trade-Off Project Scheduling Problem for Construction Projects Considering Time Value of Money." Symmetry 13, no. 12 (2021): 2402. http://dx.doi.org/10.3390/sym13122402.

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Time, cost, and quality have been known as the project iron triangles and substantial factors in construction projects. Several studies have been conducted on time-cost-quality trade-off problems so far, however, none of them has considered the time value of money. In this paper, a multi-objective mathematical programming model is developed for time-cost-quality trade-off scheduling problems in construction projects considering the time value of money, since the time value of money, which is decreased during a long period of time, is a very important matter. Three objective functions of time,

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Mohan Sai Kumar, CH, and R. S. Valarmathi. "Atrous Convolution-Based Residual Deep CNN for Image Dehazing with Spider Monkey–Particle Swarm Optimization." Intelligent Automation & Soft Computing 37, no. 2 (2023): 1711–28. http://dx.doi.org/10.32604/iasc.2023.038113.

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Ethala, Sandhya, and Annapurani Kumarappan. "A Hybrid Spider Monkey and Hierarchical Particle Swarm Optimization Approach for Intrusion Detection on Internet of Things." Sensors 22, no. 21 (2022): 8566. http://dx.doi.org/10.3390/s22218566.

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The Internet of Things (IoT) network integrates physical objects such as sensors, networks, and electronics with software to collect and exchange data. Physical objects with a unique IP address communicate with external entities over the internet to exchange data in the network. Due to a lack of security measures, these network entities are vulnerable to severe attacks. To address this, an efficient security mechanism for dealing with the threat and detecting attacks is necessary. The proposed hybrid optimization approach combines Spider Monkey Optimization (SMO) and Hierarchical Particle Swar

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Dey, Alokananda, Sandip Dey, Siddhartha Bhattacharyya, Jan Platos, and Vaclav Snasel. "Novel quantum inspired approaches for automatic clustering of gray level images using Particle Swarm Optimization, Spider Monkey Optimization and Ageist Spider Monkey Optimization algorithms." Applied Soft Computing 88 (March 2020): 106040. http://dx.doi.org/10.1016/j.asoc.2019.106040.

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Poudel, Yam, Jeewan Phuyal, and Rajiv Kumar. "Comprehensive Study of Population Based Algorithms." American Journal of Computer Science and Technology 7, no. 4 (2024): 195–217. https://doi.org/10.11648/j.ajcst.20240704.17.

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The exponential growth of industrial enterprise has highly increased the demand for effective and efficient optimization solutions. Which is resulting to the broad use of meta heuristic algorithms. This study explores eminent bio-inspired population based optimization techniques, including Particle Swarm Optimization (PSO), Spider Monkey Optimization (SMO), Grey Wolf Optimization (GWO), Cuckoo Search Optimization (CSO), Grasshopper Optimization Algorithm (GOA), and Ant Colony Optimization (ACO). These methods which are inspired by natural and biological phenomena, offer revolutionary problems

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Fateen, Seif-Eddeen K., and Adrian Bonilla-Petriciolet. "On the Effectiveness of Nature-Inspired Metaheuristic Algorithms for Performing Phase Equilibrium Thermodynamic Calculations." Scientific World Journal 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/374510.

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The search for reliable and efficient global optimization algorithms for solving phase stability and phase equilibrium problems in applied thermodynamics is an ongoing area of research. In this study, we evaluated and compared the reliability and efficiency of eight selected nature-inspired metaheuristic algorithms for solving difficult phase stability and phase equilibrium problems. These algorithms are the cuckoo search (CS), intelligent firefly (IFA), bat (BA), artificial bee colony (ABC), MAKHA, a hybrid between monkey algorithm and krill herd algorithm, covariance matrix adaptation evolut

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DAS, SUPRIO, SHAMIK SURAL, and ARUN K. MAJUMDAR. "TOWARD ANALYZING THE IMPACT OF ADVERTISEMENT BILLBOARDS ON SOCCER TELECAST VIEWERS." International Journal of Computational Intelligence and Applications 09, no. 03 (2010): 241–69. http://dx.doi.org/10.1142/s1469026810002872.

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Important soccer tournaments like the World Cup and the European Cup are broadcast to billions of people across the world. Therefore, advertising through billboards surrounding the playing arena in a soccer match is very attractive for promoting the brand image of a company. Analysis of strength and weakness of such an advertisement is helpful for the sponsors since a lot of money is spent on it and due to its potential impact on a large number of viewers at the same time. In this paper, we present a two-stage fuzzy system for analyzing the visual impact of advertisement billboards in soccer t

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Al-Zoubi, Asem S., Anas Atef Amaireh, and Nihad I. Dib. "Comparative and comprehensive study of linear antenna arrays’ synthesis." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2645. http://dx.doi.org/10.11591/ijece.v12i3.pp2645-2654.

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<span>In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; g

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Asem, S. Al-Zoubi, Atef Amaireh Anas, and I. Dib Nihad. "Comparative and comprehensive study of linear antenna arrays' synthesis." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (2022): 2645–54. https://doi.org/10.11591/ijece.v12i3.pp2645-2654.

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In this paper, a comparative and comprehensive study of synthesizing linear antenna array (LAA) designs, is presented. Different desired objectives are considered in this paper; reducing the maximum sidelobe radiation pattern (i.e., pencil-beam pattern), controlling the first null beamwidth (FNBW), and imposing nulls at specific angles in some designs, which are accomplished by optimizing different array parameters (feed current amplitudes, feed current phase, and array elements positions). Three different optimization algorithms are proposed in order to achieve the wanted goals; grasshopper o

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Reddy Chada, Sampath, and Narsimha Gugulothu. "Secure and Energy Aware Cluster based Routing using Trust Centric – Multiobjective Black Widow Optimization for large scale WSN." International journal of electrical and computer engineering systems 13, no. 7 (2022): 525–32. http://dx.doi.org/10.32985/ijeces.13.7.4.

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Wireless Sensor Network (WSN) is a promising approach that is developed for a wide range of applications due to its low installation cost. However, the nodes in the WSN are susceptible to different security threats, because these nodes are located in hostile or harsh environments. Moreover, an inappropriate selection of routing path affects the data delivery of the WSN. The important goal of this paper is to obtain secure data transmission while minimizing energy consumption. In this paper, Trust Centric - Multiobjective Black Widow Optimization (TC-MBWO) is proposed for selection of Secure Cl

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Machariah Denis, Cheruiyot Dennis, and Mundia S. "XG Boost-driven feature selection for Paygo loan default optimized using hybrid meta-heuristic algorithms." International Journal of Science and Research Archive 14, no. 1 (2025): 034–42. https://doi.org/10.30574/ijsra.2025.14.1.2317.

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Customer default is a persistent challenge impacting the loan repayment sector, particularly in the Pay-As-You-Go within Africa's renewable energy sector. In off-grid communities, renewable energy companies offer Solar Home Systems, where payments are made incrementally over time, using mobile money daily. Identifying potential defaulters early is essential for these companies' sustainability and profitability. Therefore, there is a pressing need for advanced prediction techniques to address these challenges. The primary goal of this research was to develop a hybrid meta-heuristic model that o

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Wang, Shuwen, Yang Yu, Shuangxia Liu, and David Barton. "Braking Friction Coefficient Prediction Using PSO–GRU Algorithm Based on Braking Dynamometer Testing." Lubricants 12, no. 6 (2024): 195. http://dx.doi.org/10.3390/lubricants12060195.

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The coefficients of friction (COFs) is one of the most important parameters used to evaluate the braking performance of a friction brake. Many indicators that affect the safety and comfort of automobiles are associated with brake COFs. The manufacturers of friction brakes and their components are required to spend huge amounts of time and money to carry out experimental tests to ensure the COFs of a newly developed braking system meet the required standards. In order to save time and costs for the development of new friction brake applications, the GRU (Gate Recurrent Unit) algorithm optimized

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Karunanidy, Dinesh, Rajakumar Ramalingam, Ankur Dumka, et al. "An Intelligent Optimized Route-Discovery Model for IoT-Based VANETs." Processes 9, no. 12 (2021): 2171. http://dx.doi.org/10.3390/pr9122171.

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Intelligent Transportation system are becoming an interesting research area, after Internet of Things (IoT)-based sensors have been effectively incorporated in vehicular ad hoc networks (VANETs). The optimal route discovery in a VANET plays a vital role in establishing reliable communication in uplink and downlink direction. Thus, efficient optimal path discovery without a loop-free route makes network communication more efficient. Therefore, this challenge is addressed by nature-inspired optimization algorithms because of their simplicity and flexibility for solving different kinds of optimiz

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Paryati and Prabhdeep Singh. "Adoption of Blockchain Technology for Data Management of Human Resource Demands in Organizational Enterprises." International Journal of Data Informatics and Intelligent Computing 3, no. 2 (2024): 1–15. http://dx.doi.org/10.59461/ijdiic.v3i2.104.

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Human resource data accuracy has become a significant factor in assessing the effectiveness and performance of human resource management (HRM) in businesses. Numerous human resource hazards originating from asymmetric information continue to cost firms money and even put companies out of business despite the rapid progress of mobile technology and Internet technology. Blockchain is a transaction platform that makes use of the immutability qualities of immutable data records. Because of the dispersed nature of this technology, it has a broad variety of applications in numerous industries. Seein

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Surniandari, Artika, Hilda Rachmi, Suparni Suparni, Lisda Widiastuti, and Haryani Haryani. "Classification of Gimbal Stabilizer Products Using Naive Bayes Classification." Jurnal Informatika 9, no. 2 (2022): 180–86. http://dx.doi.org/10.31294/inf.v9i2.14064.

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Menjadi videografer adalah hobi yang populer di masa pandemi ini karena berkreasi dalam bentuk video dan konten di YouTube menjadi alternatif selain sekedar mengisi waktu luang atau menghasilkan uang. Untuk mendukung kamera diperlukan perangkat pendukung, dalam hal ini seiring berjalannya waktu kamera yang mumpuni juga bisa didapatkan dari perangkat smartphone, teknologi perangkat tersebut harus diimbangi dengan kemampuan pengguna dalam mengoperasikannya. Gimbal Stabilizer salah satu jawabannya, menggunakan gimbal stabilizer menjadi salah satu alternatif karena dapat meredam getaran sehingga g

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M A Khadar Baba, Sandeep P, M. Shoukath Ali. "Evaluation of Beamforming Optimization Techniques on Multibeam Antenna for 5G wireless Communications." Journal of Information Systems Engineering and Management 10, no. 29s (2025): 703–12. https://doi.org/10.52783/jisem.v10i29s.4585.

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With the rapid evolution of 5G wireless communications, the demand for efficient and reliable Multibeam Antenna (MBA) systems has increased significantly. Beamforming optimization techniques play a crucial role in maximizing the performance of these antenna systems. This paper presents an evaluation of three popular optimization algorithms, Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC), and Spider Monkey Optimization (SMO), applied to beamforming optimization in an MBA for 5G wireless communications. The evaluation of these techniques is conducted based on several performance

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Efeoğlu, Ebru. "An Artificial Intelligence-Based Hybrid Approach to Detect the Type of Buried Objects with Broad Frequency Band Antenna Systems." Firat University Journal of Experimental and Computational Engineering 3, no. 3 (2024): 362–78. http://dx.doi.org/10.62520/fujece.1476716.

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Knowing the type of buried object before excavation prevents unnecessary excavation. Moreover, it saves time and money. In this study, an experiment set was prepared for the detection of buried objects. The experimental set was composed of an antenna that sends and receives electromagnetic waves in a wide frequency band, software that records and processes reflections, and a sandbox. In the study, metallic and non-metallic objects with different depths, sizes and shapes were buried in this sand pool and measurements were taken along a profile. 2D images were created from the measurements and i

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A. Salim, Husam, and Jabbar R. Rashed. "Feasibility Study of Off-Grid Rural Electrification in Iraq: A Case Study of the AL-Teeb Area." Iraqi Journal for Electrical and Electronic Engineering 21, no. 1 (2025): 251–63. https://doi.org/10.37917/ijeee.21.1.24.

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In developing nations, such as Iraq, supplying power to isolated and rural border areas that are not connected to the grid continues to be a problem. At present, fossil fuels, which are significant causes of pollution, supply around 80% of the world’s energy demands. Nonetheless, drastically reducing reliance on fossil fuels has many reasons, including depleting global fossil fuel supplies, increasing costs and growing energy needs. The present study examines the electrical requirements of the Al-Teeb area, a city situated in the eastern region of Iraq, close to the Iranian border. This region

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Rehman, Sana, Bilal Khan, Jawad Arif, et al. "Bi-Directional Mutual Energy Trade between Smart Grid and Energy Districts Using Renewable Energy Credits." Sensors 21, no. 9 (2021): 3088. http://dx.doi.org/10.3390/s21093088.

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A central authority, in a conventional centralized energy trading market, superintends energy and financial transactions. The central authority manages and controls transparent energy trading between producer and consumer, imposes a penalty in case of contract violation, and disburses numerous rewards. However, the management and control through the third party pose a significant threat to the security and privacy of consumers’/producers’ (participants) profiles. The energy transactions between participants involving central authority utilize users’ time, money, and impose a computational burd

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Lee, Jin-Gu, Seyha Chim, and Ho-Hyun Park. "Energy-Efficient Cluster-Head Selection for Wireless Sensor Networks Using Sampling-Based Spider Monkey Optimization." Sensors 19, no. 23 (2019): 5281. http://dx.doi.org/10.3390/s19235281.

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Extending the lifetime and stability of wireless sensor networks (WSNs) through efficient energy consumption remains challenging. Though clustering has improved energy efficiency through cluster-head selection, its application is still complicated. In existing cluster-head selection methods, the locations where cluster-heads are desirable are first searched. Next, the nodes closest to these locations are selected as the cluster-heads. This location-based approach causes problems such as increased computation, poor selection accuracy, and the selection of duplicate nodes. To solve these problem

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Mandekolu, Balakrishna Yashoda, and Vrinda Shivashetty. "Device-to-device based path selection for post disaster communication using hybrid intelligence." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (2024): 796–810. https://doi.org/10.11591/ijece.v14i1.pp796-810.

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Public safety network communication methods are concurrence with emerging networks to provide enhanced strategies and services for catastrophe management. If the cellular network is damaged after a calamity, a new-generation network like the internet of things (IoT) is ready to assure network access. In this paper, we suggested a framework of hybrid intelligence to find and re-connect the isolated nodes to the functional area to save life. We look at a situation in which the devices in the hazard region can constantly monitor the radio environment to self-detect the occurrence of a disaster, s

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M., Balakrishna Yashoda, and Vrinda Shivashetty. "Energy-efficient device-to-device communication in internet of things using hybrid optimization technique." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5418–30. https://doi.org/10.11591/ijece.v13i5.pp5418-5430.

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Device-to-device (D2D) communication has grown into notoriety as a critical component of the internet of things (IoT). One of the primary limitations of IoT devices is restricted battery source. D2D communication is the direct contact between the participating devices that improves the data rate and delivers the data quickly by consuming less battery. An energy-efficient communication method is required to enhance the communication lifetime of the network by reducing the node energy dissipation. The clustering-based D2D communication method is maximally acceptable to boom the durability of a n

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Ajay, P., B. Nagaraj, and J. Jaya. "Smart Spider Monkey Optimization (SSMO) for Energy-Based Cluster-Head Selection Adapted for Biomedical Engineering Applications." Contrast Media & Molecular Imaging 2022 (January 30, 2022): 1–13. http://dx.doi.org/10.1155/2022/2538115.

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Using energy efficiency to increase the life and sustainability of wireless sensor networks (WSNs) for biomedical applications is still a challenge. Clustering has boosted energy productivity by allowing cluster heads to be categorized, but its implementation is still a challenge. Existing cluster head selection criteria start with determining acceptable cluster head locations. The cluster heads are picked from the nodes that are most closely connected with these places. This location-based paradigm incorporates challenges such as faster processing, less precise selection, and redundant node s

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Balakrishna, Yashoda Mandekolu, and Vrinda Shivashetty. "Device-to-device based path selection for post disaster communication using hybrid intelligence." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 1 (2024): 796. http://dx.doi.org/10.11591/ijece.v14i1.pp796-810.

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Public safety network communication methods are concurrence with emerging networks to provide enhanced strategies and services for catastrophe management. If the cellular network is damaged after a calamity, a new-generation network like the internet of things (IoT) is ready to assure network access. In this paper, we suggested a framework of hybrid intelligence to find and re-connect the isolated nodes to the functional area to save life. We look at a situation in which the devices in the hazard region can constantly monitor the radio environment to self-detect the occurrence of a disaster, s

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M. Balakrishna, Yashoda, and Vrinda Shivashetty. "Energy-efficient device-to-device communication in internet of things using hybrid optimization technique." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 5 (2023): 5418. http://dx.doi.org/10.11591/ijece.v13i5.pp5418-5430.

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<span lang="EN-US">Device-to-device (D2D) communication has grown into notoriety as a critical component of the internet of things (IoT). One of the primary limitations of IoT devices is restricted battery source. D2D communication is the direct contact between the participating devices that improves the data rate and delivers the data quickly by consuming less battery. An energy-efficient communication method is required to enhance the communication lifetime of the network by reducing the node energy dissipation. The clustering-based D2D communication method is maximally acceptable to b

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Nagarajan, Vengatajalapathi, Ayyappan Solaiyappan, Siva Kumar Mahalingam, et al. "Meta-Heuristic Technique-Based Parametric Optimization for Electrochemical Machining of Monel 400 Alloys to Investigate the Material Removal Rate and the Sludge." Applied Sciences 12, no. 6 (2022): 2793. http://dx.doi.org/10.3390/app12062793.

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Electrochemical machining (ECM) is a preferred advanced machining process for machining Monel 400 alloys. During the machining, the toxic nickel hydroxides in the sludge are formed. Therefore, it becomes necessary to determine the optimum ECM process parameters that minimize the nickel presence (NP) emission in the sludge while maximizing the material removal rate (MRR). In this investigation, the predominant ECM process parameters, such as the applied voltage, flow rate, and electrolyte concentration, were controlled to study their effect on the performance measures (i.e., MRR and NP). A meta

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Dihmani, Hanane, Abdelmajid Bousselham, and Omar Bouattane. "A New Computer Aided Diagnosis for Breast Cancer Detection of Thermograms Using Metaheuristic Algorithms and Explainable AI." Algorithms 17, no. 10 (2024): 462. http://dx.doi.org/10.3390/a17100462.

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Advances in the early detection of breast cancer and treatment improvements have significantly increased survival rates. Traditional screening methods, including mammography, MRI, ultrasound, and biopsies, while effective, often come with high costs and risks. Recently, thermal imaging has gained attention due to its minimal risks compared to mammography, although it is not widely adopted as a primary detection tool since it depends on identifying skin temperature changes and lesions. The advent of machine learning (ML) and deep learning (DL) has enhanced the effectiveness of breast cancer det

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Karim, Aasam Abdul, Nor Ashidi Mat Isa, and Wei Hong Lim. "Hovering Swarm Particle Swarm Optimization." IEEE Access 9 (2021): 115719–49. http://dx.doi.org/10.1109/access.2021.3106062.

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Venter, Gerhard, and Jaroslaw Sobieszczanski-Sobieski. "Particle Swarm Optimization." AIAA Journal 41, no. 8 (2003): 1583–89. http://dx.doi.org/10.2514/2.2111.

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Poli, Riccardo, James Kennedy, and Tim Blackwell. "Particle swarm optimization." Swarm Intelligence 1, no. 1 (2007): 33–57. http://dx.doi.org/10.1007/s11721-007-0002-0.

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Dorigo, Marco, Marco Oca, and Andries Engelbrecht. "Particle swarm optimization." Scholarpedia 3, no. 11 (2008): 1486. http://dx.doi.org/10.4249/scholarpedia.1486.

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Kumar, Manoj, Jyoti Raman, and Priya Priya. "Particle Swarm Optimization." International Journal of Materials Forming and Machining Processes 2, no. 1 (2015): 54–87. http://dx.doi.org/10.4018/ijmfmp.2015010104.

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In this paper, particle swarm optimization, which is a recently developed evolutionary algorithm, is used to optimize parameters in surface grinding processes where multiple conflicting objectives are present. The relationships between surface grinding process parameters and the performance measures of interest are obtained by using experimental data and particle swarm optimization intelligent neural network systems (PSOINNS). The results showed that particle swarm optimization is an effective method for solving multi-objective optimization problems, and an integrated system of neural networks

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LIU, Huai-liang, Rui-juan SU, Ruo-ning XU, and Ying GAO. "Cooperative particle swarm optimization." Journal of Computer Applications 29, no. 11 (2009): 3068–73. http://dx.doi.org/10.3724/sp.j.1087.2009.03068.

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Zhi-Hui Zhan, Jun Zhang, Yun Li, and H. S. H. Chung. "Adaptive Particle Swarm Optimization." IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39, no. 6 (2009): 1362–81. http://dx.doi.org/10.1109/tsmcb.2009.2015956.

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Ferreira de Carvalho, Danilo, and Carmelo José Albanez Bastos‐Filho. "Clan particle swarm optimization." International Journal of Intelligent Computing and Cybernetics 2, no. 2 (2009): 197–227. http://dx.doi.org/10.1108/17563780910959875.

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