Article
Engineering, Multidisciplinary
Elsayed Badr, Sultan Almotairi, Mustafa Abdul Salam, Hagar Ahmed
Summary: The study presents a novel approach to improve breast cancer diagnosis accuracy, including enhancing support vector machine performance, introducing new scaling techniques, and utilizing parallel techniques to enhance efficiency.
ALEXANDRIA ENGINEERING JOURNAL
(2022)
Article
Computer Science, Artificial Intelligence
Zhuo Wang, Pengjian Shang, Xuegeng Mao
Summary: In this paper, the cumulative residual Tsallis singular entropy (CRTSE) is introduced to measure the complex characteristics of nonlinear signals. The effectiveness and robustness of CRTSE are verified through simulation experiments. The proposed CRTSE-GWOSVM model based on grey wolf optimized support vector machine (GWOSVM) can effectively and accurately identify complex systems.
EXPERT SYSTEMS WITH APPLICATIONS
(2024)
Article
Geosciences, Multidisciplinary
Peng He, Wenjing Wu
Summary: A novel prediction model, LGWO-SVR, is proposed for forecasting dam displacements, which combines support vector regression and Levy flight-based grey wolf optimizer. The model is validated with multiple-arch dam as a case study and compared with other algorithms. Results show that the LGWO-SVR model has high accuracy, stability, and prediction rate, making it suitable for dam engineering applications.
FRONTIERS IN EARTH SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Fereshteh Jeyafzam, Babak Vaziri, Mohsen Yaghoubi Suraki, Ali Asghar Rahmani Hosseinabadi, Adam Slowik
Summary: In medical science, collecting and classifying data from various diseases pose challenges, especially in diagnosing conditions like diabetes which can lead to severe complications. Machine learning methods, such as support vector machine, can be used to predict diabetes complications by adjusting parameters through optimization algorithms.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Meng Liu, Kaiping Luo, Junhuan Zhang, Shengli Chen
Summary: The study shows that the hybrid algorithm combining grey wolf optimizer and support vector machine can help achieve stable excess returns, improve the predictive performance of the support vector regression machine, and achieve better profitability and reliability in the Chinese A-share market.
EXPERT SYSTEMS WITH APPLICATIONS
(2021)
Article
Computer Science, Interdisciplinary Applications
Haiqing Yang, Zhihui Wang, Kanglei Song
Summary: A new hybrid intelligence technique was introduced to predict the performance of the full-face tunnel boring machine (TBM). By measuring and considering the important parameters, a predictive model was established and evaluated. The results showed that the model had high accuracy in predicting the TBM performance.
ENGINEERING WITH COMPUTERS
(2022)
Article
Computer Science, Interdisciplinary Applications
Jian Zhou, Shuai Huang, Mingzheng Wang, Yingui Qiu
Summary: This study proposes two support vector machine models for predicting soil liquefaction potential, optimized by genetic algorithm and grey wolf optimizer. The results show that the GWO-SVM model achieved the highest classification accuracy on three data sets and outperformed the GA-SVM model.
ENGINEERING WITH COMPUTERS
(2022)
Article
Social Sciences, Interdisciplinary
Xin Ma, Yanqiao Deng, Hong Yuan
Summary: Natural gas is crucial in China's energy system reconstruction, and accurate forecasting of its supply and consumption indicators is important for decision-making by the government and energy companies. This study proposes a Grey Wavelet Support Vector Regressor model that combines the grey system model and support vector regression model for handling the complex features of Chinese natural gas datasets. The proposed model outperforms other models in out-of-sample forecasting, demonstrating its high potential in predicting natural gas supply and consumption in China.
Article
Energy & Fuels
Shuang Li, Kun Xu, Guangzhe Xue, Jiao Liu, Zhengquan Xu
Summary: An improved grey wolf optimized support vector regression model for predicting coal spontaneous combustion temperature is proposed in this study, considering the characteristics of prediction data samples and the timeliness of applicable models. The effectiveness of the improved grey wolf optimizer algorithm is verified by numerical experiments, showing stronger global search ability, faster convergence speed, and better stability. The proposed prediction model has significant advantages in accuracy and stability, providing better decision reference for predicting and warning coal spontaneous combustion fires in coal mines.
Article
Construction & Building Technology
Hongfang Lu, Saleh Behbahani, Xin Ma, Tom Iseley
Summary: A hybrid model combining multi-objective grey wolf optimizer and support vector machine was proposed to predict composite material properties in six datasets. The results showed that the model performed well in property prediction, and the prediction accuracy was closely related to the amount of data in the training set.
CONSTRUCTION AND BUILDING MATERIALS
(2021)
Article
Environmental Sciences
Li Li, Zhongxu Zhang, Dongsheng Zhao, Yue Qiang, Bo Ni, Hengbin Wu, Shengchao Hu, Hanjie Lin
Summary: This study proposes an improved prediction model to estimate the scale of debris flows, and validates its effectiveness using data from Beichuan County. The results demonstrate strong predictive capabilities and improved accuracy in predicting the scale of debris flows. Additionally, the study identifies key factors that influence the scale of debris flows in Beichuan County.
Article
Environmental Sciences
Ru Liu, Jianbing Peng, Yanqiu Leng, Saro Lee, Mahdi Panahi, Wei Chen, Xia Zhao
Summary: This study evaluates landslide susceptibility in Zhenping County using a hybrid model, combining SVR with GWO and FA, based on a database of landslides and various conditioning factors. The results show that the SVR-GWO model performs the best in spatial prediction of landslides, followed by SVR-FA and SVR models. The hybrid models improve the performance of the single SVR model and show good prospects for regional-scale landslide spatial modeling.
Article
Engineering, Civil
Youngje Choi, Jungwon Ji, Eunkyung Lee, Sunmi Lee, Sooyeon Yi, Jaeeung Yi
Summary: Climate change affects water demand and supply, leading to more severe droughts and floods. To address this, the South Korean government added a water supply function to the Hwacheon reservoir that was originally built for hydropower. However, a water supply rule curve is missing. In this study, we develop a rule curve using optimization techniques and evaluate its performance compared to the firm supply method. The results show that the developed rule curve performs better and the Improved Grey Wolf Optimizer algorithm is the most effective.
WATER RESOURCES MANAGEMENT
(2023)
Article
Acoustics
Ismail Shahin, Osama Ahmad Alomari, Ali Bou Nassif, Imad Afyouni, Ibrahim Abaker Hashem, Ashraf Elnagar
Summary: Nowadays, the analysis and interpretation of emotions in human speech communication have gained significant attention in the field of human-computer interaction. Various speech recognition systems have been proposed to recognize the emotional states of speakers through their speech recordings. Feature extraction is a critical step in building an emotion recognition system, but not all extracted features are relevant for classifying emotions accurately. This study introduces an intelligent feature selection method called GWO-KNN, which uses a bio-inspired optimization algorithm and a K-nearest neighbor classifier to enhance the classification performance of emotion recognition systems by identifying the most relevant subset of features. The proposed method outperforms classical methods and recent state-of-the-art approaches on three different databases.
Article
Engineering, Mechanical
Maolin Shi
Summary: This study proposes a decision tree-assisted support vector regression method, which can improve prediction accuracy by using training samples partition. Experimental results show that it has competitive prediction results compared with traditional methods.
JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY
(2022)
Article
Chemistry, Physical
Rajalaxmi Sahoo, C. Reshma, D. S. Shankar Rao, C. V. Yelamaggad, S. Krishna Prasad
Summary: This study investigates the influence of the flexible spacer parity of a guest photoactive liquid crystalline dimer on the photonic bandgap features of the cholesteric and twist grain boundary smectic C phases of the host molecule. The results show that the parity of the photoactive dimer affects the width of the photonic bandgap and the blue-shift of the cholesteric phase. Additionally, the parity of the dimer also affects the layer spacing and two-dimensional periodicity of the liquid crystalline phases.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Sara Rozas, Alberto Gutierrez, Mert Atilhan, Alfredo Bol, Santiago Aparicio
Summary: This study presents a multiscale theoretical investigation on the use of bifunctional hydrophobic Deep Eutectic Solvent for carbon capture using tetrapropylammonium chloride, acetic acid, and ethanolamine. The characterization includes nanoscale analysis of CO2 absorption mechanisms and changes in liquid phase properties during gas capture.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Tabouli Eric Da-yang, Alhadji Malloum, Jean Jules Fifen, Mama Nsangou, Jeanet Conradie
Summary: In this study, the potential energy of different glycine tautomers and their interaction with Cu2+ cations was investigated. The results showed that the solvation medium and the presence of Cu2+ cations influenced the stability of glycine tautomers.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Xiaoliang Gou, Nan Ye, Qingqing Han, Junjie Cui, Long Yi Jin
Summary: In this study, amphiphilic rod-coil molecules with rigid DSA parts and flexible oligoether chains were designed and their assembly capacities were investigated. The morphology of the molecular aggregates was influenced by the pH of the solution and UV light, and the aggregates showed adsorption capacity for nitroaromatic compounds.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Shuang Liu, Liyan Shan, Cong Qi, Wenhui Zhang, Guannan Li, Bei Wang, Wei Wei
Summary: Optimizing the design of styrene-butadiene-styrene copolymer (SBS) is crucial for producing cost-effective SBS modifiers and improving road quality. This study examined the influence of SBS content and molecular structure on viscosity and compatibility. The results showed that the viscosity contribution of SBS is determined by its molecular structure and phase morphology.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Artem A. Petrov, Ekaterina A. Titova, Aydar A. Akhmadiyarov, Ilnaz T. Rakipov, Boris N. Solomonov
Summary: This work focuses on the thermochemistry of solvation of azeotropes. The enthalpies of dissolution of azeotropes in different mediums were determined, and the impact of the structure of the azeotropes on their properties in solution was discussed. A correlation between enthalpies of solvation and molar refraction was used to determine the vaporization enthalpies of azeotropes for the first time. The results were found to be consistent with literature data, obtained using direct and calculated methods. These findings contribute to the analysis of the structure-property relationships of azeotropes.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
L. V. Kamaeva, E. N. Tsiok, N. M. Chtchelkatchev
Summary: Understanding the correlations between liquids and solids allows us to predict the thermodynamic parameter range favorable for the formation of intriguing solid phases by studying liquids. In this study, we experimentally and theoretically investigated an Al-Cu-Co system within different composition ranges, and identified high-temperature solid phases. Our findings demonstrated the correlation between the boundaries of different solid phases and undercooling and viscosity in the concentration area.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
R. Aneesh Kumar, S. Jamelah Al-Otaibi, Y. Sheena Mary, Y. Shyma Mary, Nivedita Acharjee, Renjith Thomas, Renjith Raveendran Pillai, T. L. Leena
Summary: In this study, the interactions between doped and pristine coronenes and adenine nucleobases were investigated using Density Functional Theory. The optimal configurations, adsorption energies, charge transfer, and electrical properties of each complex were calculated. It was found that doped coronene had stronger adsorption strength and charge transfer compared to pristine coronene. The stability of the complexes was attributed to non-covalent interactions in the interactive region. The change in electrical conductivity of coronenes after adsorption suggested their sensitivity towards DNA bases. The predicted energy gap and prolonged recovery time for adenine-coronene configurations indicated the potential application of pristine/doped coronene in DNA detection.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Gang Zhou, Yongwei Liu, Biao Sun, Zengxin Liu, Cuicui Xu, Rulin Liu, Qi Zhang, Yongmei Wang
Summary: The CFD-DEM method was used to simulate the dust deposition pattern in the bronchus of anchor digging drivers, revealing the highest dust concentration in the vortex region of the working face. The study also found a positive correlation between dust particle diameter and bronchial deposition rate, and a negative correlation with alveolar deposition rate.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Yan Zhang, Yafei Luo, Lingkai Tang, Mingyan E, Jianping Hu
Summary: This study investigates the effects of different transition metal decorations on B12N12 nanocages on the adsorption properties of nitrosourea drugs using computational methods. The results reveal the presence of weak non-covalent interactions between metals and nanocages, and the interaction between drugs and nanocages plays a significant role in drug adsorption. Compared to free drugs, the adsorption of drugs on nanocages can facilitate electron transfer, reduce energy gaps and chemical hardness, indicating activity at the target site.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
C. I. Alcolado, J. Poblete, L. Garcia-Rio, E. Jimenez, F. J. Poblete
Summary: In this study, the selective oxidation of aromatic aldehydes was investigated using Ru(VI) as a catalyst and hexacyanoferrate (III) as a cooxidant in an alkaline medium. The reaction mechanism involves complex reaction orders for the oxidant and the aromatic aldehyde, while the reaction order for Ru(VI) is one. The proposed mechanism includes two catalytic cycles and the formation and decomposition of complexes. Quantitative structure-activity relationship analysis showed that deactivating groups in the para-position enhance the process.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Inez A. Barbieri, Marcos L. S. Oliveira, Franciele S. Bruckmann, Theodoro R. Salles, Leonardo Zancanaro, Luis F. O. Silva, Guilherme L. Dotto, Eder C. Lima, Mu. Naushad, Cristiano R. Bohn Rhoden
Summary: This study evaluated the adsorption of zolpidem on magnetic graphene oxide and synthesized magnetic graphene oxide adsorbents for zolpidem removal. The best magnetic nanoadsorbent was found to have a removal percentage of 87.07% at specific pH and temperature conditions. The results suggest that the removal of zolpidem is related to the surface chemistry of the adsorbent rather than the surface area of graphene oxide. The adsorbent showed excellent adsorption efficiency and magnetic behavior, making it a promising material for removing zolpidem from aqueous solutions.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Hongyan Huang, Chunquan Li, Siyuan Huang, Yuling Shang
Summary: This study examines the sensitivity of the thermal conductivity of water-based alumina nanofluids to changes in concentration, sphericity, and temperature. The results show that volume fraction and temperature have a significant impact on the thermal conductivity, while sphericity also needs to be considered. A support vector machine regression model was created to analyze the sensitivity of the thermal conductivity to different parameters. The findings indicate that temperature, sphericity, and volume fraction are the most sensitive variables.
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Correction
Chemistry, Physical
V. M. Pergamenshchik, T. Bryk, A. Trokhymchuk
JOURNAL OF MOLECULAR LIQUIDS
(2024)
Article
Chemistry, Physical
Valentyn Rudenko, Anatolii Tolochko, Svitlana Bugaychuk, Dmytro Zhulai, Gertruda Klimusheva, Galina Yaremchuk, Tatyana Mirnaya, Yuriy Garbovskiy
Summary: This paper reports on the synthesis, structural characterization, spectral and nonlinear-optical properties of glass nanocomposites made of glass forming ionic liquid crystals and nanoparticles. The study reveals that by exciting the nanocomposites within their absorption band, a control over effective optical nonlinearities can be achieved, allowing the modification of the magnitude and sign of the effective nonlinear absorption coefficient. The proposed strategy using metal-alkanoates based glass-forming ionic liquid crystals and nanoparticles shows great potential for the development of nanophotonics and plasmonics technologies.
JOURNAL OF MOLECULAR LIQUIDS
(2024)