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By Vanessa Viterbo, Lia Walker, Hassan Khaniani, Vitor Viterbo

Fatigue is a major contributor to haul-truck incidents in mining, with up to 65% of fatigue-related events associated with operator drowsiness or microsleep episodes, Williamson et al. (2011) and Caterpillar (2007). This study examines whether operator fatigue produces measurable and repeatable signatures in haul-truck telemetry. Eight confirmed fatigue-related disengagement events were analyzed using 20-minute telemetry windows centered around the incident. Statistical descriptors, Z-score normalization, first- and second-order derivatives, sliding-window variability, and cross-signal correlations were extracted from engine speed, throttle position, fuel rate, ground speed, and brake indicators. A logistic regression classifier was trained and evaluated using leave-one-event-out cross-validation. The model achieved a receiver operating characteristic (ROC) area under the curve (AUC) scores of 0.75–0.79, demonstrating consistent discriminative capability. A characteristic shutdown sequence characterized by sudden throttle collapse, fuel-rate decay, RPM reduction, and unbraked coasting was observed across all events, indicating operator disengagement rather than mechanical malfunction. Earlywarning indicators appeared 90–500 seconds before shutdown in the events analyzed, suggesting practical potential for real-time fatigue prediction. These findings provide initial evidence that telemetry-based fatigue detection is feasible and could enhance safety in mining operations.

Feb 22, 2026

By Bright Oppong Afum, Kojo Boakye, Kwaku Boakye

This research developed and simulated a novel multi-indicator Fatigue Detection and Alert System (FDAS) designed to enhance fatigue detection accuracy in mining environments. The system integrates a comprehensive set of inputs: eye blink rate, eye closure duration, yawning frequency, distraction levels, Pre-shift Check-in Scores (Self-report) and Electroencephalography (EEG) Levels. Using MATLAB’s Fuzzy Logic Rule Viewer (FLRV) and Simulink, simulations demonstrated the FDAS’s robust ability to process these diverse physiological and behavioural indicators accurately. It effectively classified operator fatigue into low, moderate, and high fatigue levels, consistently providing appropriate outputs and corresponding intervention recommendations across various mixed-signal scenarios. The system achieved a calculated accuracy of 85.19% across 27 test entries, with a standard deviation of approximately 1.8459, confirming its reliability for real-time fatigue monitoring. These findings highlight the significant potential of this fuzzy logicbased approach to proactively identify early signs of fatigue, substantially enhancing safety and operational efficiency in demanding mining operations.

Feb 22, 2026

By Sakshi Hazuria Anderson, Angela Binder, Oscar Jaime Restrepo Baena, Simit Raval, Sandra Nowosad

As the mining industry faces times of change, new challenges arise to ensure raw material supply for future generations. Different scenarios are currently shaping the way we mine and teach mining engineering. Led by an increasing demand for raw materials, net-zero requirements for improving long-term operation performance, technological advancements such as automation and digitalization, safety improvements, environmental considerations and a need for social acceptance, mining is pursuing to change and adapt to these requirements at a faster pace. Such changing times raise new concerns, one of the most relevant is the lower number of students interested or enrolling in mining engineering and related fields, leaving mining engineering as one of the less preferred career options for students. Nonetheless, it is essential to continue addressing and supplying the skill sets that are suited to the contemporary and future mining industry. To this end, globally, academia is currently undergoing several initiatives such as curricula updates and adaptation, upskilling, improving teaching practices and techniques, including e-learning techniques, enhancing industry-academia and inter-university collaboration, and much more. In countries like Australia, where mining plays a crucial role in the economy, the need for curriculum updates is more pressing than ever. As the mining industry evolves with new technologies and sustainable practices, there is a growing demand for a workforce skilled in these modern approaches. Recognizing this necessity, universities such as the University of New South Wales and Curtin University have taken significant steps to revamp their educational programs. By updating their academic offerings, both universities aim to equip graduates with the necessary skills to drive innovation and sustainability in mining, supporting Australia’s development as a leader in this critical sector. Moreover, the selection of topics that drive curricula update and the focus of the research institutions in mining engineering must extend beyond mere technological and technical aspects to include social and ethical dimensions. In this context, the Universidad Nacional de Colombia, in association with the Colorado School of Mines, has introduced the topic of humanitarian engineering (HE) in 2020. HE is a sociotechnical approach that focuses on developing engineering solutions that promote the sustainable development of communities addressing their basic needs and aiming to improve their quality of life (Menéndez-Aguado et al., 2023; Smith et al., 2023). By focusing on sustainable development, community engagement and equitable resource distribution, HE helps the industry build positive relationships with stakeholders, reduce conflicts and foster social license to operate. As the mining industry seeks sustainable and socially responsible practices, future engineers require training in this area to understand the broader impacts of their work, fostering a mindset that prioritizes community well-being and environmental stewardship alongside technical proficiency. However, developing skills toward humanitarian engineering and sustainable mining among new generations of mining professionals remains a complex task. Integrating the necessary content to prepare future engineers for the multifaceted demands of the industry into a single study program poses significant challenges. To address these complexities, modern educational approaches such as the ones integrated in the mining engineering programs at Clausthal University of Technology can be leveraged to enhance both teaching and learning experiences (Binder, 2024b; Bothe-Fiekert et al., 2023; Nowosad et al., 2024). Innovative teaching methods, such as blended-learning, project-based learning, case studies, scenario simulations and interdisciplinary collaborations, can help bridge gaps by fostering critical thinking, creativity and empathy among students. By embracing modern pedagogical strategies, institutions can better equip future engineers to navigate the evolving landscape of the mining industry responsibly and effectively.

Dec 1, 2025

By Sakshi Hazuria Anderson, Angela Binder, Oscar Jaime Restrepo Baena, Simit Raval, Sandra Nowosad

As the mining industry faces times of change, new challenges arise to ensure raw material supply for the younger and future generations. Different scenarios are currently shaping the way we mine and teach mining engineering. Led by an increasing demand for raw materials, net zero requirements for improving long-term operation performance, technological advancements such as automation and digitalization, safety improvements, environmental considerations and a need for social acceptance, mining is pursuing to change and adapt to these requirements at a faster pace. Such changing times raise new concerns, one of the most relevant is the lower number of students interested or enrolling in mining engineering and related fields leaving mining engineering as one of the less preferred career options between the younger generations. Nonetheless, it is essential to continue addressing and supplying the skill sets that are suited to the contemporary and future mining industry. To this end, globally, academia is currently undergoing several initiatives such as curricula updates and adaptation, up skilling, improving teaching practices and techniques, including e-learning techniques, enhancing industry-academia and inter-university collaboration, and much more. In countries like Australia, where mining plays a crucial role in the economy, the need for curriculum updates is more pressing than ever. As the mining industry evolves with new technologies and sustainable practices, there is a growing demand for a workforce skilled in these modern approaches. Recognizing this necessity, universities such as the University of New South Wales and Curtin University have taken significant steps to revamp their educational programs. By updating their academic offerings, both universities aim to equip graduates with the necessary skills to drive innovation and sustainability in mining, supporting Australia’s development as a leader in this critical sector. Moreover, the selection of topics that drive curricula update and the focus of the research institutions in mining engineering must extend beyond mere technological and technical aspects to include social and ethical dimensions. In this context, the Universidad Nacional de Colombia, in association with the Colorado School of Mines, has introduced the topic of Humanitarian Engineering (HE) in 2020. HE is a socio-technical approach that focuses on developing engineering solutions that promote the sustainable development of communities addressing their basic needs and aiming to improve their quality of life (10, 18). By focusing on sustainable development, community engagement, and equitable resource distribution, HE helps the industry build positive relationships with stakeholders, reduce conflicts, and foster social license to operate. As the mining industry seeks sustainable and socially responsible practices, future engineers require training in this area to understand the broader impacts of their work, fostering a mindset that prioritizes community well-being and environmental stewardship alongside technical proficiency.

Feb 1, 2025

By Daniel Roy, Danielle Bouffard, Antoine Berton, Simon Gariépy

Commissioning a mineral processing plant has always been a challenging task. The process includes pre- operational verification, dry and wet commissioning, and a gradual ramp-up to full production, all of which must be executed within the shortest possible timeframe, requiring numerous highly interdependent tasks to be conducted concurrently. This phase is under scrutiny by shareholders, corporate management, and other stakeholders who are keen to see a return on investment as the operation starts yielding results. Despite extensive documentation in the literature highlighting its significance, the impact of the commissioning phase remains underestimated in contemporary mining projects. This paper provides an overview of the commissioning process and its associated challenges before focusing on a critical success factor: building a dedicated commissioning team with the required competencies and personality profiles. The roadmap to achieving an efficient plant start-up is outlined. Drawing on over 15 years of experience with more than 20 concentrator commissioning and start-ups, a general framework is presented to maximize success. This method emphasizes the crucial role of the operation and metallurgy team in supporting these projects. Finally, insights from Soutex’s involvement in multiple start-ups are shared, offering lessons learned that emphasize best practices and challenges encountered in expediting the ramp-up process while maintaining high Health, Safety, and Environment (HSE) standards.

Feb 1, 2025

By Aleksandar D. Bugarski, Dylan A. Ritter

The results of laboratory characterization of tailpipe emissions for three “clean” engines that meet U.S. EPA Tier 4 final emissions standards were used to assess the viability and effectiveness of repowering existing engines and powering new mobile equipment with those engines as a control strategy for reducing exposure of underground miners to diesel aerosol and criteria gases. The evaluated engines were representative of those that achieve the emission standards through implementation of various in-cylinder emissions control strategies, use of crankcase filtration, and use of three types of exhaust aftertreatment systems: (1) diesel oxidation catalytic converter (DOC), (2) combination of DOC and the full-flow wall flow monolith diesel particulate filter (DPF), or (3) combination of DOC, diesel exhaust fluid (DEF) based selective catalytic reduction (SCR) system, and ammonia slip catalyst (ASC). The study showed that the highest reductions in concentrations of diesel aerosols in underground workings, in terms of both mass and number, could be achieved if the engines, preferably in all power classes, are fitted with viable DPF systems. The use of U.S. EPA Tier 4 final engines equipped with DOC and DOC/SCR/ASC systems could help operators to considerably reduce mass, but not number concentrations of aerosols. The emissions of two of the evaluated engines, one equipped with DOC and the other equipped with DOC/DPF systems, were characterized by substantial secondary NO2 emissions that would limit the viability of those engines for underground mining applications. It appears that the catalyst formulations used in the exhaust aftertreatment systems of the “clean” engines marketed to the underground mining industry need to be formulated to minimize the potential for generation of secondary NO2 emissions. The results indicate that the engines fitted with viable SCR/ASC systems present a low-NO2 alternative. All three “clean” engines were found to have low CO output. Therefore, due to nuances associated with the use of diesel-powered mobile equipment in underground mines, special attention needs to be paid to the selection and potentially optimization of “clean” engines for underground mining applications.

Feb 1, 2025

By SME SME

NORTH AMERICAN TUNNELING 2024 PROCEEDINGS

Jun 23, 2024

By Joseph Goessling, Mark Kroncke, James Parkes

The I-35 Capital Expressway (CapEx) Central Drainage Tunnels will serve as a stormwater collection system for the forthcoming I-35 Capital Express Central reconstruction project through downtown Austin, Texas. The schematic level concept design included three tunnels, 10 to 14 ft ID, totaling 26,000 LF. Constructability reviews during design development indicated issues with the concept design including phasing of construction, conicts with future retaining walls, staging area concerns, and signicant mixed face tunneling. The design was updated to mitigate these risks. The revised design includes two tunnels, both 22-ft ID and totaling 33,000 LF, that will be mined almost entirely in rock.

Jun 23, 2024

By Irwan Halim, Bhoshaga Mitrran Ravi Chandran, Kevin Huynh

Tunnel segmental lining design constitutes a significant iterative process where modeling and numerical analysis are factors in deciding the number of segments, their dimensions, gasket placements, as well as the locations of dowels and bolts. Consequently, these modifications lead to revisions in the final drawing details. However, the current tunnel engineering practices lack systematic solutions that effectively bridge the gap between the iterative design process and efficient visualization of completed drawings due to the time- consuming nature of redrawing. This paper presents a pioneering application of AI-driven solutions including using Autodesk's API, for the Northside Interceptor Tunnel (NSIT) Project. It showcases the automation of drawing design and the real-time visualization of modifications, thereby streamlining the drawing process.

Jun 23, 2024

By Georges Cote, Ehsan Alavi, Eren Kusdogan

The City of Toronto's Coxwell Bypass Tunnel is currently being constructed by North Tunnel Constructors (NTC) ULC, a joint venture of Jay Dee Canada, C&M McNally Tunnel Constructors and Michels Canada. This project includes construction of approximately 10.5 km of 6.3 meter finished diameter rock tunnel, five 20 meter diameter storage shafts and eleven tunnel connection drop shafts, along with associated deaeration and adit tunnels. 120 m of Starter tunnel and 70 m of Tail tunnel were excavated with roadheaders to help with the launch of the TBM and as part of the contract base scope work. JayDee Canada in Collaboration with Everest Equipment Co. developed an innovative approach to design and build a stand-alone Ring Machine Erector nicknamed Enterprise to erect precast segmental lining in Starter and Tail tunnels in lieu of Cast-In- Place concrete. This paper describes the design and provides feedback on the innovative procedure used to install the rings.

Jun 23, 2024

By Xie Junjie, Li Shina, Ma Ruixin, Min Changli, Yin Zichen, Li Kang, Shi Zhuonan

Cesium and rubidium were effectively separated by zinc ferrocyanide coprecipitation method, and the effect of precipitant addition amount on the separation of cesium and rubidium was studied. Under the conditions of Zn/Cs molar ratio of 0.45 and Zn/Fe molar ratio of 1, the precipitation rate of cesium is 84.01% and the separation factor of Cs/Rb is 164.65. The thermogravimetric curves of the sediment were measured, and the effects of roasting temperature, roasting time, and leaching liquid/ solid ratio on the extraction of cesium were studied. Almost all of the cesium was extracted under optimal conditions: roasting temperature of 600 °C, roasting time of 3 h, leaching temperature of 25 °C, leaching time of 0.5 h, and liquid/solid ratio of 5:1 mL/g. After the leaching process, the leach liquor with high concentration of cesium of 80.17 g/L was obtained. Finally, the leach liquor was further purified by solvent extraction, and the purity of the cesium chloride product reached 99.66%.

Mar 17, 2024

By Yao Yevenyo Ziggah, Victor Amoako Temeng, Solomon Evans Kweku Koomson

Tyre hours/life deficit is a major operational challenge facing the mining industry which adversely affects materials production and costs. An accurate forecast of the tyre life is key in addressing this menace. This study for the first time employed the hybrid intelligent technique by utilising three metaheuristic optimisation algorithms, including particle swarm optimisation (PSO), genetic algorithm (GA), and whale optimisation algorithm (WOA), as trainers for the parametric weights and biases to optimise multilayer perceptron neural network (MLPNN) for enhancing prediction of on-site dump truck tyre life in the mine. Four hybrid models known as PSO-MLPNN, WOA-MLPNN, GA-MLPNN, and BP-MLPNN were developed using a total of 157 tyre dataset records obtained from a surface mine in Ghana. In assessing the prediction performances for the models developed, five statistical performance metrics of variance accounted for (VAF), Nash–Sutcliffe efficiency index (NASH), coefficient of determination (r2), mean absolute percentage error (MAPE), and correlation coefficient (r) were utilised. Moreover, ranking, uncertainty analysis and Bayesian information criterion (BIC) techniques were utilised to establish the most effective hybrid model, whereas sensitivity analysis was conducted on the input parameters. Results achieved showed that PSO-MLPNN was the best for prediction because it had the least MAPE value of 1.196% and relatively high values of VAF (99.642%), NASH (0.996), r2 (0.996), and r (0.998). Besides, PSO-MLPNN had the best selection criteria values of 6, 7.1725, and 444.834 for the ranking, uncertainty analysis and BIC respectively. Hence, PSO-MLPNN is recommended for the prediction of on-site dump truck tyre life for the studied mine.

Mar 11, 2024

By Wei Victor Liu, Omer Faruk Ugurlu, Chengkai Fan, Bei Jiang

The accurate prediction of truck productivity plays a pivotal role in improving the efficiency and profitability of open-pit mining operations. However, predicting truck productivity is challenging owing to the complex nature of the working conditions of the mine site. This paper proposes a deep neural network model to overcome the challenge of predicting truck productivity in open-pit mines. The prediction model was built using eight variables and was optimized by considering different train-test split ratios, numbers of hidden layers and neurons, and activation functions. The proposed model's performance was evaluated using various metrics and was compared with other commonly used machine learning algorithms. According to the results, the proposed model outperformed traditional machine learning algorithms by achieving higher accuracy and lower error rates, with the best-performing model having four hidden layers with 70 neurons per layer and a scaled exponential linear unit activation function, resulting in a coefficient of determination value of 0.89. This demonstrates the potential of deep neural network models for predicting truck productivity in open-pit mine sites. Moreover, a single variable sensitivity analysis was conducted to investigate the impact of input variables on truck productivity. The results show that haul distance is the most influential variable for the prediction of truck productivity.

Feb 12, 2024

By Jupneek Singh, Zachary A. Kiehl, Leila Safazadeh, Gareth Kennedy, Eleonora Widzyk-Capehart, Jeremy W. Ward

Mine workers are continuously exposed to a host of nonfatal stressors and potentially fatal hazards: noise exposure, excessive vibration, poor air quality, toxicant exposure, ignition of combustible gases, equipment-related accidents, and thermal heat stress. Wearable or portable sensors and contextual analytics provide a platform to unobtrusively collect and fuse multimodal health and safety data in real time to compute both acute safety and longitudinal health insights. This paper presents preliminary trial results, conducted by Simtars, VigiLife, Inc., and Queensland Mines Rescue Service, of the application of wearable sensors to monitor heat stress and other vital biometrics for mines rescue personnel.

Feb 1, 2024

By William H. Langer

I spent 41 years as a geologist with the US Geological Survey (USGS) conducting geologic studies and preparing peer reviewed maps and reports describing the results of those studies. Since retiring from the USGS in 2011, I have been a consultant specializing in aggregates and other industrial minerals. Consequently, I have had the opportunity and pleasure to apply the information contained in those kinds of geologic maps and reports to real-life situations. About half of my consulting is performing due diligence for mineral resource evaluations of one type or another where resource information has been provided by the property owner. Many of those jobs necessitate that I conduct desktop studies followed by field work. I then use my information to review and comment on the written reports of others; reports variably referred to as geologic reports, resource studies, reserve analyses, and so forth. While there are many well written reports addressing geologic resource issues, I was surprised to see that there are also a significant number of so-called geologic reports that only pay cursory attention to geology. Unfortunately, that lack of rigorous geologic investigation commonly leads to erroneous conclusions. This paper addresses three such reports covering concrete sand, metallurgical gravel, and proppants (frac sand). Although all three examples are located in the Gulf Coastal Plain Province, I do not reveal the exact location of any of the properties for purposes of confidentiality. Furthermore, I have generalized the site descriptions and illustrations. However, all the descriptions faithfully define the geologic situation.

Feb 1, 2024

By Brianna Eiter, Max Barham, Tim Bauerle

Fatigue-related risk is a persistent safety concern for the mining industry. However, fatigue and sleepiness are often treated interchangeably, which can lead to confusion and potentially less effective reduction of safety risk. To provide clarity, we present an overview of similarities and differences between work-related fatigue risk and sleepiness including definitions, theories, measurements, and mitigation strategies. As a supplement, a summative visual model which highlights these similarities and differences is presented. Expanding industry knowledge in this area will assist safety professionals in crafting more targeted risk management practices appropriate for work-related fatigue risk, sleepiness, or both.

Dec 19, 2023

By Frank Pepe, Nestor Garavelli

The 2023 Rapid Excavation and Tunneling Conference (RETC) will be held in Boston, MA and will include the presentation of 133 papers divided into 20 technical sessions during the 3 day conference that were selected from over 200+ papers that were submitted to the committee. The selected papers are included within this book to provide a comprehensive recap of the conference while also providing a source of reference for contractors and engineers in the future. The selected papers will include contributions from all divisions of the tunneling industry plus risk management and best contract practices. Boston is known to the tunneling industry for its complex and difficult tunneling history, specifically of recent memory the Central Artery/Tunnel Project also know as the “Big Dig” of the 1980s and early 1990s. The selection of Boston as a host city was fitting from a historical perspective and as avenue for the city to present its upcoming tunnel projects. RETC began in 1972 with the idea of sharing ideas, design and project construction experience, and new technology, between contractors, designers, owners and suppliers. The ability to provide a single location every other year for all facets of the tunneling industry to gather and discuss the aforementioned was and still is viewed as a way to help the tunnel industry grow. The lessons learned from completed projects, the advancement of technology which could be implemented into design and the presentation of new projects by owners/designers and contractors allows for the limits and complexity of upcoming projects to be expanded beyond our current capabilities. Our industry has never been as busy as it currently is, and we are seeing more future projects coming out for solicitation across all business sectors. With the good fortune that all of us have been blessed with one of the biggest challenges that we have been faced with is the shortage of future management on all levels for our projects including the labor force. We all want our industry to continue to grow and succeed, our most important assets are the people that we employ. Investing in the education and continued training of our work forces to be up to date with the latest technology and methods is the key to our success. This also includes develop, recruiting and mentoring of young students graduating college to join our industry so that we can all continue to grow. We hope that all those attending the conference will have the ability to attend as many sessions as possible and to expand their network within our industry. As in past years, scholarship students will be in attendance and we encourage all to offer these students an opportunity to visit jobs, attend learning sessions or future internships to expand their interest in our industry that needs an injection of young engineers to contribute and lead our future Rapid Excavation and Tunneling Conferences. The program chairs wish to thank the session chairs, co-chairs, authors, and other members of the RETC Executive Committee for their dedication to this conference. Last but certainly not least, we give special thanks to the SME staff for their hard work and enthusiastic support in making this conference possible.

Dec 1, 2023

By Turker Hudaverdi, Yasar Agan

This study tries to predict blast-induced flyrock using intelligent modelling techniques. Flyrock is a site-specific phenomenon. Design variables and rock properties highly influence flyrock throw distance. Site investigations were conducted in a sandstone quarry. Fundamental operational parameters, blast dimensions, bench face condition, and rock mass structure were monitored. Stepwise regression technique was applied for variable selection. Burden–hole diameter ratio, in situ block size, and powder factor were determined as the most significant parameters. Considering output of stepwise regression, artificial neural network, ANFIS, and Gaussian process regression techniques were applied to predict flyrock throw. A comprehensive validation was performed using twelve different performance indices. Pre-determination of input parameters supported development of successful soft computing applications. Rock block size was found to be an appropriate input variable for flyrock modelling. In addition to classical performance indices, standardized and symmetric accuracy metrics were quite useful in model validation process. The intelligent models predict flyrock range with an error less than 6 m. The mean percentage errors are lower than 10%. ANFIS seems to be the best model for flyrock prediction. The calculated mean absolute error is 5.36 for ANFIS model.

Nov 12, 2023

By Arman Hazrathosseini, Ali Moradi Afrapoli

Fleet management systems (FMSs) as the pivotal part of any surface mining operation find it essential to evolve from conventional into intelligent systems because of both Mining 4.0 requirements and some shortcomings inherent in conventional methods. However, this novel transformation needs to be investigated technically and strategically. To this end, the previously published research works on intelligent FMSs are explored to track the latest status of these third generation frameworks within the surface mining context. Following that, their underlying models are compared in terms of five categories of allocation and dispatching features to pinpoint the technical gaps ignored. Having drawn the future lines of research, the present article then leverages the popular SWOT analysis method to outline the strengths, weaknesses, opportunities, and threats associated with the advent of these intelligent FMSs in mines of future. By and large, the analysis indicates that advantages outweigh disadvantages. Solutions are offered to address the existing weaknesses and threats.

Nov 10, 2023

By Weiran Zuo, Jinsheng Guo, Chun Yu, Jinyu Zhan, Bao Guo

High-precision prediction of the target minerals’ content in the feed and concentrate products is vitally important for the efficient beneficiation of mineral resources. Visible and near-infrared (NIR) spectroscopy provides a cost-effective way for online measurement of the mineral content in an industrial process. In this investigation, simulated specimens consisting of five different types of minerals that are present in the copper oxide ore, malachite, quartz, calcite, hematite, and chlorite were prepared with a variety of malachite contents, and the mixed specimens were analyzed by a visible-NIR spectrometer in an integral sphere mode. The reflectance spectrum is used as input and the malachite content as output to build the prediction model. The obtained data was modeled by support vector machines (SVM), and a Grey Wolf Optimization (GWO) is proposed with the goal of improving the prediction accuracy. The GWO algorithm has been applied to adaptively search for the best combination of featured values. After cyclic comparison, the optimal penalty factors c and g can be quickly and accurately selected. The experimental results show that the SVM model established by the GWO algorithm has a better fitting effect and smaller prediction error, compared with other models.

Aug 3, 2023