Different Meta-Heuristic Optimized Radial Basis Function Neural Network Models for Short-Term Power Consumption Forecasting by Dhivagar Shanmugam, V Ramana

“…Specifically, the coefficient of determination (R²) values for the training, testing, and total datasets are 0.9994, 0.9920, and 0.9985, respectively, demonstrating that AGWO is the most precise optimizer among the studied meta-heuristic algorithms.…”
Get full text

Hybrid LSTM-PSO optimization techniques for enhancing wind power bidding efficiency in electricity markets by Viet Anh Truong, Ngoc Sang Dinh, Thanh Long Duong, Ngoc Thien Le, Cong Dinh Truong, Linh Tung Nguyen

“…Past research has predominantly focused on utilizing meta-heuristic algorithms to optimize neural network structures, while the exploration of deep learning in optimization has remained relatively limited. …”
Get full text

Design and Analysis of FOPID-Based Damping Controllers Using a Modified Grey Wolf Optimization Algorithm by Manoj Kumar Kar, Sanjay Kumar, Arun Kumar Singh, Sibarama Panigrahi, Murthy Cherukuri

“…The results obtained from the MGWOA-tuned FOPID-based damping controllers are compared with those obtained using recently developed efficient and competitive heuristic algorithms. It was observed that the MGWOA method is well-suited for damping low-frequency oscillations. …”
Get full text

A Bayesian Neural Network-Based Method to Calibrate Microscopic Traffic Simulators by Qinqin Chen, Anning Ni, Chunqin Zhang, Jinghui Wang, Guangnian Xiao, Cenxin Yu

“…Based on the BNN model with the best performance, heuristic algorithms (HAs) are performed to seek the optimal values of the parameters to be calibrated with the minimum difference between the predicted results of BNN and the field-measured values. …”
Get full text

Comprehensive influence evaluation algorithm of complex network nodes based on global-local attributes by Weijin JIANG, Ying YANG, Tiantian LUO, Wenying ZHOU, En LI, Xiaowei ZHANG

“…Mining key nodes in the network plays a great role in the evolution of information dissemination, virus marketing, and public opinion control, etc.The identification of key nodes can effectively help to control network attacks, detect financial risks, suppress the spread of viruses diseases and rumors, and prevent terrorist attacks.In order to break through the limitations of existing node influence assessment methods with high algorithmic complexity and low accuracy, as well as one-sided perspective of assessing the intrinsic action mechanism of evaluation metrics, a comprehensive influence (CI) assessment algorithm for identifying critical nodes was proposed, which simultaneously processes the local and global topology of the network to perform node importance.The global attributes in the algorithm consider the information entropy of neighboring nodes and the shortest distance nodes between nodes to represent the local attributes of nodes, and the weight ratio of global and local attributes was adjusted by a parameter.By using the SIR (susceptible infected recovered) model and Kendall correlation coefficient as evaluation criteria, experimental analysis on real-world networks of different scales shows that the proposed method is superior to some well-known heuristic algorithms such as betweenness centrality (BC), closeness centrality (CC), gravity index centrality(GIC), and global structure model (GSM), and has better ranking monotonicity, more stable metric results, more adaptable to network topologies, and is applicable to most of the real networks with different structure of real networks.…”
Get full text

Millimeter-Wave Underlay D2D Communications: Channel Assignment, Transmission mode Selection and Power Control for Full-CSI and Limited-CSI Scenarios by Nima Reisi

“…As the optimization problem is mixed-integer-non-linear programming, two heuristic algorithms are proposed, assuming full Channel Side Information (CSI) and limited CSI at Base Station, respectively. …”
Get full text

Influence maximization algorithm based on social network by Xuan WANG, Yu ZHANG, Junfeng ZHOU, Ziyang CHEN

“…The influence maximization (IM) problem asks for a group of seed users in a social network under a given propagation model, so that the information spread is maximized through these users.Existing algorithms have two main problems.Firstly, these algorithms were difficult to be applied in large-scale social networks due to limited expected influence and high time complexity.Secondly, these algorithms were limited to specific propagation models and could only solve the IM problem under a single type of social network.When they were used in different types of networks, the effect was poor.In this regard, an efficient algorithm (MTIM) based on two classic propagation models and reverse influence sampling (RIS) was proposed.To verify the effectiveness of MTIM, experiments were conducted to compare MTIM with greedy algorithms such as IMM, TIM and PMC, and heuristic algorithms such as OneHop and Degree Discount on four real social networks.The results show that MTIM can return a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML"> <mrow><mo>(</mo> <mrow> <mn>1</mn><mo>−</mo><mfrac> <mn>1</mn> <mtext>e</mtext> </mfrac> <mo>−</mo><mi>ε</mi></mrow> <mo>)</mo></mrow></math></inline-formula> approximate solution, effectively expand the expected influence and significantly improve the efficiency.…”
Get full text

Interpretable real-time monitoring of short-term rockbursts in underground spaces based on microseismic activities by Mohammad Hossein Kadkhodaei, Ebrahim Ghasemi

“…Abstract In this study, two novel hybrid intelligent models were developed to evaluate the short-term rockburst using the random forest (RF) method and two meta-heuristic algorithms, whale optimization algorithm (WOA) and coati optimization algorithm (COA), for hyperparameter tuning. …”
Get full text

Adaptive Gradient-Based Optimization Method for Parameter Identification in Power Distribution Network by Bin Li, Yehai Jiang, Ke Hu, Xiangyi Zhou, Haoran Chen, Shihe Xu, Hao Jiao, Jinming Chen

“…By comparing the proposed method and several heuristic algorithms, it is found that the errors in both three criteria via our solution are much lower with a much smoother and more stable convergence of loss function. …”
Get full text

Current development and future prospects of multi-target assignment problem: A bibliometric analysis review by Shuangxi Liu, Zehuai Lin, Wei Huang, Binbin Yan

“…Subsequently, existing solution algorithms for the MTA problem are reviewed, generally falling into three categories: exact algorithms, heuristic algorithms, and machine learning algorithms. Finally, a development framework is proposed based on the ''HIGH'' model (high-speed, integrated, great, harmonious) to guide future research and intelligent weapon system development concerning the MTA problem. …”
Get full text

Nature-Inspired Metaheuristics for Two-Agent Scheduling with Due Date and Release Time by Hongwei Li, Yuvraj Gajpal, Chirag Surti, Dongliang Cai, Amit Kumar Bhardwaj

“…This paper provides mathematical models, heuristic algorithms, and two nature-based metaheuristic algorithms to solve the problem. …”
Get full text

Estimation of Ultimate Bearing Capacity in Rock-Socketed Piles Using Optimized Machine Learning Approaches by Ali Hassan, Hamza Rashid

“…To enhance the model's precision, the study incorporates two state-of-the-art meta-heuristic algorithms, the Artificial Hummingbird Algorithm (AHA) and the Improved Grey Wolf Optimizer (IGWO), into the analysis. …”
Get full text

Self-Administered Information Sharing Framework Using Bioinspired Mechanisms by Huibo Bi, Yanyan Chen, Wen-Long Shang, Chengcheng Song, Wenbo Huang

“…Previous research mainly focuses on investigating novel protocols to save energy by reducing data traffic with the aid of optimal or heuristic algorithms. However, data packet behaviours and significant parameters involved are mostly preconfigured in a supervised-learning fashion rather than using an unsupervised learning paradigm and therefore may not adapt to uncertain or fast-changing environments. …”
Get full text

Inverse design of nanophotonic devices enabled by optimization algorithms and deep learning: recent achievements and future prospects by Kim Junhyeong, Kim Jae-Yong, Kim Jungmin, Hyeong Yun, Neseli Berkay, You Jong-Bum, Shim Joonsup, Shin Jonghwa, Park Hyo-Hoon, Kurt Hamza

“…We discuss representative methods commonly employed in nanophotonic design, including various meta-heuristic algorithms such as trajectory-based, evolutionary, and swarm-based approaches, in addition to adjoint-based optimization. …”
Get full text

Reliability-Based Optimum Design of Dome Truss Structures through Enhanced Vibration Particle System by Pedram Hosseini, Nasibeh Hatami, Seyed Rohollah Hoseini Vaez

“…Also, reliability index 3 is set as the minimum target reliability index. Meta-heuristic algorithms can be used to achieve optimal design and appropriate safety since mathematical calculations are time-consuming. …”
Get full text

Soft computing paradigm for climate change adaptation and mitigation in Iran, Pakistan, and Turkey: A systematic review by Muhammad Talha, A. Pouyan Nejadhashemi, Kieron Moller

“…Although some articles utilized multiple techniques, classical ML methods appeared in approximately 37.3 % of the studies, neural network paradigms in about 57.5 %, and optimization or meta-heuristic algorithms in around 5.0 %. Regarding thematic focus, about 33.3 % of the articles addressed water resource management, 22.2 % focused on climate prediction, 11.1 % on land and agriculture, 9 % on ecosystem modeling, and 24.2 % on natural disaster preparedness and response. …”
Get full text

Multiobjective Salp Swarm Algorithm Approach for Transmission Congestion Management by Anjali Agrawal, Seema N. Pandey, Laxmi Srivastava, Pratima Walde, R. K. Saket, Baseem Khan

“…To examine the proposed approach, it has been implemented on IEEE 30-bus system and a bigger power system IEEE 118-bus system; as well as the proposed technique of MOSSA has been compared and found better than reported methods and two other meta heuristic algorithms (multiobjective modified sperm swarm optimization and multiobjective adoptive rat swarm optimization).…”
Get full text

FANT: Flexible Attention-Shifting Network Telemetry by Mingwei Cui, Yufan Peng, Fan Yang

“…To further save bandwidth, we model the attention-shifting process and apply heuristic algorithms to solve it. Our experiments show that FANT effectively supports the operation of ANT network applications. …”
Get full text

Novel Optimization Algorithms Usage to Model the Compressive Strength of Ultra-High-Performance Concrete in Machine Learning Technique: Support Vector Regression by Tianhua Zhou, Dorota Mozyrska

“…In addition, two meta-heuristic algorithms have been used for improving the accuracy of predicting CS containing the Marine Predator Algorithm (MPA) and Grasshopper Optimization Algorithm (GOA). …”
Get full text

Hybrid Henry Gas-Harris Hawks Comprehensive-Opposition Algorithm for Task Scheduling in Cloud Computing by Nora Omran Alkaam, Abu Bakar Md Sultan, Masnida B. Hussin, Khaironi Yatim Sharif

“…This highlights the effectiveness of hybrid meta-heuristic algorithms in achieving a balance between exploration and exploitation, preventing them from getting stuck in local optima.…”
Get full text