Article
Computer Science, Artificial Intelligence
Sanchari Deb, Xiao-Zhi Gao
Summary: Transportation electrification is seen as a viable solution to global warming, air pollution, and energy crisis, but the optimal placement of charging infrastructure for Electric Vehicles presents a complex problem involving multiple design variables, objective functions, and constraints.
COMPLEX & INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Dickson Odhiambo Owuor, Thomas Runkler, Anne Laurent, Joseph Onderi Orero, Edmond Odhiambo Menya
Summary: Gradual pattern extraction is a field in Knowledge Discovery in Databases that aims to map correlations between attributes of a data set as gradual dependencies. In this study, three population-based optimization techniques are investigated to improve the efficiency of mining gradual patterns. The results show that ant colony optimization technique outperforms genetic algorithm and particle swarm optimization in the task of gradual pattern mining.
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
(2021)
Article
Computer Science, Artificial Intelligence
Ya-Hui Jia, Yi Mei, Mengjie Zhang
Summary: This article focuses on the capacitated electric vehicle routing problem and proposes a confidence-based bilevel ant colony optimization algorithm to solve it. The algorithm divides the problem into two subproblems: capacitated VRP and fixed routing vehicle charging problem. Experimental results show that the proposed algorithm has reached the state-of-the-art level and achieved new best-known solutions.
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION
(2022)
Article
Automation & Control Systems
Xiangbing Zhou, Hongjiang Ma, Jianggang Gu, Huiling Chen, Wu Deng
Summary: This paper proposes a parameter adaptation-based ant colony optimization (ACO) algorithm called PF3SACO, which combines particle swarm optimization (PSO), fuzzy system, and 3-Opt algorithm to improve the optimization ability and convergence, and avoid falling into local optima. The PF3SACO utilizes dynamic parameter adjustment and adaptive search to achieve better optimization performance, and applies 3-Opt algorithm to optimize the generated path.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Automation & Control Systems
Serap Ercan Comert, Harun Resit Yazgan
Summary: This paper introduces three multi-objective electric vehicle routing problems that consider different charging strategies and electric vehicle charger types while optimizing five conflicting objectives. A new hierarchical approach consisting of Hybrid Ant Colony Optimization (HACO) and Artificial Bee Colony Algorithm (ABCA) is developed to solve these problems. The proposed approach is examined on test-based instances and achieves the best new results in most cases.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Yisheng An, Yuxin Gao, Naiqi Wu, Jiawei Zhu, Hongzhang Li, Jinhui Yang
Summary: As the number of electric vehicles increases, scheduling the charging operations of EVs in urban areas becomes an important issue. This paper investigates the EV charging problem at the scheduling level and proposes a mathematical model and scheduling algorithms to improve charging efficiency.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Software Engineering
Vandana Reddy, P. Gayathri
Summary: This article introduces a method for solving the energy conservation problem in wireless sensor networks through the combination of ant colony optimization and glowworm swarm optimization algorithms. The algorithm achieves energy saving and efficient data collection by analyzing the network and accessing the swarm heads.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2022)
Article
Environmental Sciences
Yongkun Zhou, Dan Song, Bowen Ding, Bin Rao, Man Su, Wei Wang
Summary: This paper studies the problem of passive localization using a UAV swarm. A passive localization method based on an ant colony pheromone mechanism is proposed, which utilizes local interactions among individuals to process observation data. Experimental results show that the proposed method achieves higher accuracy than traditional localization algorithms.
Article
Automation & Control Systems
Ya-Hui Jia, Yi Mei, Mengjie Zhang
Summary: The development of electric vehicle techniques has brought about a new vehicle routing problem, the capacitated EV routing problem (CEVRP). To address the challenges presented by the limited number of charging stations and cruising range of EVs, a novel bilevel ant colony optimization algorithm is proposed in this article. By dividing CEVRP into capacitated VRP and fixed route vehicle charging problem, the algorithm significantly outperforms state-of-the-art algorithms on various benchmark instances.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Computer Science, Theory & Methods
Joshua Peake, Martyn Amos, Nicholas Costen, Giovanni Masala, Huw Lloyd
Summary: This paper presents an improved algorithm for the Virtual Machine Placement (VMP) problem, which significantly improves the solution speed by utilizing parallelization techniques and modern processor technologies. The algorithm achieves solution qualities comparable to or even superior to other nature-inspired methods.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Mathematics
Alessandro Niccolai, Francesco Grimaccia, Marco Mussetta, Riccardo Zich, Alessandro Gandelli
Summary: Reflectarray antennas are low-profile high-gain systems widely used in the aerospace industry. The design complexity and the need for high scanning capabilities have led to the development of an optimization environment that can be applied with evolutionary optimization algorithms.
Article
Energy & Fuels
Adel Oubelaid, Nabil Taib, Toufik Rekioua, Mohit Bajaj, Arvind Yadav, Mokhtar Shouran, Salah Kamel
Summary: A secure power management strategy has been developed for a fuel cell-supercapacitor hybrid electric vehicle to enhance reliability and comfort. The strategy detects failures, isolates the faulty source, and reconfigures the control scheme to ensure voltage stability and vehicle traction. The use of a particle swarm optimization algorithm enables simultaneous tuning of vehicle speed and torque controllers, minimizing torque and speed ripples.
FRONTIERS IN ENERGY RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Mohamed H. Mousa, Mohamed K. Hussein
Summary: This paper proposes a UAV-based offloading strategy for IoT tasks, where IoT devices are dynamically clustered considering UAV energy and task delays. The optimization problem of determining the number of clusters and tasks is modeled as a mixed-integer, nonlinear constraint optimization. A discrete differential evolution algorithm is used to solve the optimization problem, and ant colony optimization is employed to find the shortest path for the UAV. The simulation results demonstrate the effectiveness of the proposed strategy in terms of task delays and UAV energy consumption.
PEERJ COMPUTER SCIENCE
(2022)
Article
Engineering, Chemical
Jin-Hwan Lee, Woo-Jung Kim, Sang-Yong Jung
Summary: This paper introduces a robust optimization algorithm tailored for the optimal design of electric machines. The algorithm, named RePSO, employs the rate of change of the cost function to ensure robustness of the optimal solution. Comparisons with traditional methods and validation through simulations and experiments demonstrate the robustness and effectiveness of the proposed algorithm.
Article
Computer Science, Artificial Intelligence
Dimitra Trachanatzi, Manousos Rigakis, Magdalene Marinaki, Yannis Marinakis
Summary: This research addresses a challenging problem in emergency response, namely how to effectively protect crucial community assets under temporal and spatial constraints. By introducing the Modified Ant Colony System algorithm, superior solutions can be achieved within operational time limits.
SWARM AND EVOLUTIONARY COMPUTATION
(2022)
Article
Multidisciplinary Sciences
Muhammad Rabani Mohd Romlay, Azhar Mohd Ibrahim, Siti Fauziah Toha, Philippe De Wilde, Ibrahim Venkat
Summary: The paper proposes a novel Clustered Extraction and Centroid Based Clustered Extraction Method (CE-CBCE) for feature extraction followed by a convolutional neural network (CNN) object classifier. The integration of the CE-CBCE and CNN methods allows for accurate detection utilizing lightweight actuated LiDAR input with low computing means. The final results show a reliable accuracy of 97% based on genuine LiDAR data.
Article
Chemistry, Analytical
Galang P. N. Hakim, Mohamed Hadi Habaebi, Siti Fauziah Toha, Mohamed Rafiqul Islam, Siti Hajar Binti Yusoff, Erry Yulian Triblas Adesta, Rabeya Anzum
Summary: This study introduces and analyzes the behavior of the LoRa pathloss propagation model for wireless sensor networks in remote and isolated tropical areas. The developed Fuzzy ANFIS model achieves the best performance in near ground propagation compared to other benchmark models, as validated by statistical analysis tools.
Article
Energy & Fuels
Yacine Merrad, Mohamed Hadi Habaebi, Siti Fauziah Toha, Md Rafiqul Islam, Teddy Surya Gunawan, Mokhtaria Mesri
Summary: Recent advances in technology and the adoption of renewable energy sources have transformed traditional power grids into smart grids, enabling consumers to also become energy producers. The integration of blockchain technology has allowed for decentralized peer-to-peer energy trading. However, there is a conflict of interest between prosumers and distribution system operators, highlighting the need for a solution that achieves optimal power flow.
Review
Geosciences, Multidisciplinary
Intiaz Mohammad Abir, Azhar Mohd Ibrahim, Siti Fauziah Toha, Amir Akramin Shafie
Summary: This paper summarizes the main literature studies on hospital evacuation simulation and discusses the importance of assisted evacuation. The study found that existing models are capable of accurately simulating hospital evacuation, but most of them use rule-based AI instead of self-learning AI. The possibilities of self-learning AI should be explored further.
INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION
(2022)
Article
Engineering, Multidisciplinary
Mohammed Rafeeq, Siti Fauziah Toha, Salmiah Ahmad, Mohd Asyraf Mord Razib
Summary: This paper presents a kinematic model of an amphibious robot with multi-mode motion capability. Simulation analysis demonstrates the robot's enhanced maneuverability and balance, providing a theoretical basis for motion control and optimization algorithms.
IIUM ENGINEERING JOURNAL
(2022)
Article
Electrochemistry
Md Azizul Hoque, Mohd Khair Hassan, Abdulrahman Hajjo, Mohammad Osman Tokhi
Summary: In this paper, a battery lifetime degradation model is proposed at an accelerated current rate (C-rate). The model is evaluated using deep learning algorithms and it is shown that the LSTM-RNN model has superior performance at accelerated C-rate compared to the traditional FNN network.
Article
Energy & Fuels
Anith Khairunnisa Ghazali, Mohd Khair Hassan, Mohd Amran Mohd Radzi, Azizan As'arry
Summary: Recycling braking energy is crucial for enhancing the energy efficiency of electric vehicles. This study investigates a parallel-distribution braking system that transfers as much energy as possible from the wheel to the battery and proposes an integrated braking force distribution strategy with gain-scheduling super-twisting sliding mode control. Simulation results validate the effectiveness of the proposed control strategy in practical applications.
Review
Green & Sustainable Science & Technology
Ahmed Hassan Saad, Haslinda Nahazanan, Badronnisa Yusuf, Siti Fauziah Toha, Ahmed Alnuaim, Ahmed El-Mouchi, Mohamed Elseknidy, Angham Ali Mohammed
Summary: Based on the extensive evaluation of published studies, there is a lack of research on systematic literature reviews related to machine learning prediction techniques and methodologies in soil improvement using green materials. However, literature review suggests that machine learning algorithms are effective in predicting various soil characteristics. The current study aims to comprehensively evaluate recent breakthroughs in machine learning algorithms for soil improvement using the PRISMA systematic procedure and meta-analysis, which will advance the understanding of civil and geotechnical designers and practitioners in integrating data for geotechnical engineering problems.
Article
Multidisciplinary Sciences
Md Azizul Hoque, Mohd Khair Hassan, Abdulraman Hajjo, Tsuyoshi Okita
Summary: This research tested lithium-ion batteries at different charge and discharge rates and proposed a capacity fade model to interpret their vulnerabilities in energy storage systems. The study found that charging and discharging the batteries at accelerated rates accelerates their aging. Furthermore, the capacity fade model was investigated using deep learning algorithms and it was discovered that the LSTM-RNN battery aging model performed better than the conventional FNN network.
ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
(2023)
Proceedings Paper
Green & Sustainable Science & Technology
A. Taha Taha, Mohd Khair Hassan, Noor Izzri Abdul Wahab, Hussein I. Zaynal
Summary: This study introduces a new Red Deer Algorithm (RDA) optimization technique for minimizing total harmonic distortion (THD) in multilevel inverters (MLIs). RDA belongs to the class of swarm-based biologically inspired optimization methods. To evaluate the angles obtained through RDA optimization, a single-phase seven-level cascade multilevel inverter with symmetrical DC sources was utilized. The results showed that RDA optimization outperformed various metaheuristic algorithms in finding angles with minimum THD for the modulation index in the range of 0-1.
2023 IEEE IAS GLOBAL CONFERENCE ON RENEWABLE ENERGY AND HYDROGEN TECHNOLOGIES, GLOBCONHT
(2023)
Article
Computer Science, Information Systems
Hesham Ahmed, Azizan As'arry, Abdul Aziz Hairuddin, Mohd Khair Hassan, Yunyun Liu, Erasmus Cufe Ujunwa Onwudinjo
Summary: This paper focuses on using intelligent methods to improve the suspension system of vehicles for a comfortable driving experience. The semi-active suspension system, which utilizes an intelligent actuator and real-time controllers, outperforms other systems in dissipating unwanted vibrations. The authors propose a Fuzzy-DE-PID controller based on a modified DE algorithm to enhance the performance of the semi-active suspension system. Simulation and experimental tests demonstrate the effectiveness of the proposed controller in improving the vehicle's ride comfort.
Article
Computer Science, Information Systems
Nur Fadzilah Mohd Radzi, Azura Che Soh, Asnor Juraiza Ishak, Mohd Khair Hassan
Summary: The study explores the use of Gas Chromatography Mass Spectrometry (GCMS) in herb discrimination, suggesting the Weighted Histogram Analysis Method (WHAM) for better classification accuracy by extracting new features from minor and major volatile compound data. The application of WHAM technique results in improved discrimination between herb species in the same family group, reducing overlap and enhancing classification accuracy.
Review
Computer Science, Information Systems
Mohammed Rafeeq, Siti Fauziah Toha, Salmiah Ahmad, Mohd Asyraf Razib
Summary: Unmanned amphibious robots have shown great promise and efficiency in scientific, military, and commercial applications in the past two decades. Advancements in aquatic robotics and mobile robotics have made these robots more agile, robust, and efficient in maneuvering various environments and terrains. Inspired by nature, such as amphibians, amphibious robots offer enhanced flexibility, improved adaptability, and higher mobility across terrestrial, aquatic, and aerial mediums.
Proceedings Paper
Computer Science, Interdisciplinary Applications
Mohd Hanif Che Hasan, Mohd Khair Hassan, Fauzi Ahmad, Mohammad Hamiruce Marhaban, Sharil Izwan Haris
PROCEEDINGS OF MECHANICAL ENGINEERING RESEARCH DAY 2020 (MERD'20)
(2020)
Article
Computer Science, Information Systems
Mohammed Rafeeq, Siti Fauziah Toha, Salmiah Ahmad, Muhammad Syafiq Mohd Yusof, Mohd Asyraf Mohd Razib, Muhammad Ikmal Hakim Shamsul Bahrin
Summary: The research designs and models a paired four-legged amphibious robot with an optimized Klann linkage mechanism for leg movement. Results show that the Klann mechanism provides higher propulsion than traditional four-bar mechanisms, and dynamic analysis confirms the robot's maneuverability.
Article
Thermodynamics
Yong Cheng, Fukai Song, Lei Fu, Saishuai Dai, Zhiming Yuan, Atilla Incecik
Summary: This paper investigates the accessibility of wave energy absorption by a dual-pontoon floating breakwater integrated with hybrid-type wave energy converters (WECs) and proposes a hydraulic-pneumatic complementary energy extraction method. The performance of the system is validated through experiments and comparative analysis.
Article
Thermodynamics
Jing Gao, Chao Wang, Zhanwu Wang, Jin Lin, Runkai Zhang, Xin Wu, Guangyin Xu, Zhenfeng Wang
Summary: This study aims to establish a new integrated method for biomass cogeneration project site selection, with a focus on the application of the model in Henan Province. By integrating Geographic Information System and Multiple Criterion Decision Making methods, the study conducts site selection in two stages, providing a theoretical reference for the construction of biomass cogeneration projects.
Article
Thermodynamics
Mert Temiz, Ibrahim Dincer
Summary: The current study presents a hybrid small modular nuclear reactor and solar-based system for sustainable communities, integrating floating and bifacial photovoltaic arrays with a small modular reactor. The system efficiently generates power, hydrogen, ammonia, freshwater, and heat for residential, agricultural, and aquaculture facilities. Thermodynamic analysis shows high energy and exergy efficiencies, as well as large-scale ammonia production meeting the needs of metropolitan areas. The hybridization of nuclear and solar technologies offers advantages of reliability, environmental friendliness, and cost efficiency compared to renewable-alone and fossil-based systems.
Editorial Material
Thermodynamics
Wojciech Stanek, Wojciech Adamczyk
Article
Thermodynamics
Desheng Xu, Yanfeng Li, Tianmei Du, Hua Zhong, Youbo Huang, Lei Li, Xiangling Duanmu
Summary: This study investigates the optimization of hybrid mechanical-natural ventilation for smoke control in complex metro stations. The results show that atrium fires are more significantly impacted by outdoor temperature variations compared to concourse/platform fires. The gathered high-temperature smoke inside the atrium can reach up to 900 K under a 5 MW train fire energy release. The findings provide crucial engineering insights into integrating weather data and adaptable ventilation protocols for smoke prevention/mitigation.
Article
Thermodynamics
Da Guo, Heping Xie, Mingzhong Gao, Jianan Li, Zhiqiang He, Ling Chen, Cong Li, Le Zhao, Dingming Wang, Yiwei Zhang, Xin Fang, Guikang Liu, Zhongya Zhou, Lin Dai
Summary: This study proposes a new in-situ pressure-preserved coring tool and elaborates its pressure-preserving mechanism. The experimental and field test results demonstrate that this tool has a high pressure-preservation capability and can maintain a stable pressure in deep wells. This study provides a theoretical framework and design standards for the development of similar technologies.
Article
Thermodynamics
Aolin Lai, Qunwei Wang
Summary: This study assesses the impact of China's de-capacity policy on renewable energy development efficiency (REDE) using the Global-MSBM model and the difference-in-differences method. The findings indicate that the policy significantly enhances REDE, promoting technological advancements and marketization. Moreover, regions with stricter environmental regulations experience a higher impact.
Article
Thermodynamics
Mostafa Ghasemi, Hegazy Rezk
Summary: This study utilizes fuzzy modeling and optimization to enhance the performance of microbial fuel cells (MFCs). By simulating and analyzing experimental data sets, the ideal parameter values for increasing power density, COD elimination, and coulombic efficiency were determined. The results demonstrate that the fuzzy model and optimization methods can significantly improve the performance of MFCs.
Article
Thermodynamics
Zhang Ruan, Lianzhong Huang, Kai Wang, Ranqi Ma, Zhongyi Wang, Rui Zhang, Haoyang Zhao, Cong Wang
Summary: This paper proposes a grey box model for fuel consumption prediction of wing-diesel hybrid vessels based on feature construction. By using both parallel and series grey box modeling methods and six machine learning algorithms, twelve combinations of prediction models are established. A feature construction method based on the aerodynamic performance of the wing and the energy relationship of the hybrid system is introduced. The best combination is obtained by considering the root mean square error, and it shows improved accuracy compared to the white box model. The proposed grey box model can accurately predict the daily fuel consumption of wing-diesel hybrid vessels, contributing to operational optimization and the greenization and decarbonization of the shipping industry.
Article
Thermodynamics
Huayi Chang, Nico Heerink, Junbiao Zhang, Ke He
Summary: This study examines the interaction between off-farm employment decisions between couples and household clean energy consumption in rural China, and finds that two-paycheck households are more likely to consume clean energy. The off-farm employment of women is a key factor driving household clean energy consumption to a higher level, with wage-employed wives having a stronger influence on these decisions than self-employed ones.
Article
Thermodynamics
Hanguan Wen, Xiufeng Liu, Ming Yang, Bo Lei, Xu Cheng, Zhe Chen
Summary: Demand-side management is crucial to smart energy systems. This paper proposes a data-driven approach to understand the relationship between energy consumption patterns and household characteristics for better DSM services. The proposed method uses a clustering algorithm to generate optimal customer groups for DSM and a deep learning model for training. The model can predict the possibility of DSM membership for a given household. The results demonstrate the usefulness of weekly energy consumption data and household socio-demographic information for distinguishing consumer groups and the potential for targeted DSM strategies.
Article
Thermodynamics
Xinglan Hou, Xiuping Zhong, Shuaishuai Nie, Yafei Wang, Guigang Tu, Yingrui Ma, Kunyan Liu, Chen Chen
Summary: This study explores the feasibility of utilizing a multi-level horizontal branch well heat recovery system in the Qiabuqia geothermal field. The research systematically investigates the effects of various engineering parameters on production temperature, establishes mathematical models to describe their relationships, and evaluates the economic viability of the system. The findings demonstrate the significant economic feasibility of the multi-level branch well system.
Article
Thermodynamics
Longxin Zhang, Songtao Wang, Site Hu
Summary: This investigation reveals the influence of tip leakage flow on the modern transonic rotor and finds that the increase of tip clearance size leads to a decline in rotor performance. However, an optimal tip clearance size can extend the rotor's stall margin.
Article
Thermodynamics
Kristian Gjoka, Behzad Rismanchi, Robert H. Crawford
Summary: This paper proposes a framework for assessing the performance of 5GDHC systems and demonstrates it through a case study in a university campus in Melbourne, Australia. The results show that 5GDHC systems are a cost-effective and environmentally viable solution in mild climates, and their successful implementation in Australia can create new market opportunities and potential adoption in other countries with similar climatic conditions.
Article
Thermodynamics
Jianwei Li, Guotai Wang, Panpan Yang, Yongshuang Wen, Leian Zhang, Rujun Song, Chengwei Hou
Summary: This study proposes an orientation-adaptive electromagnetic energy harvester by introducing a rotatable bluff body, which allows for self-regulation to cater for changing wind flow direction. Experimental results show that the output power of the energy harvester can be greatly enhanced with increased rotatory inertia of the rotating bluff body, providing a promising solution for harnessing wind-induced vibration energy.
