ECONOMICS OF UNDERUTILIZED CROP PRODUCTION IN AKOKNORTH WEST LOCAL GOVERNMENTAREA, ONDO STATE, NIGERIA: A CASE STUDY OF PIGEON PEA (Cajanus cajan) by Olutope Stephen OJO

“…The estimated coefficient of labour was negative and significant at 1 percent alpha level and the estimated coefficient of agrochemical, and quantity produce were positive and significant at 1 percent alpha level, indicating that increase in this variable will increase output and profit of pigeon pea of the constraints affecting pigeon pea farming poor road network was ranked the 1st and land problem was ranked 12th. …”
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Optimizing Cold Chain Logistics with Artificial Intelligence of Things (AIoT): A Model for Reducing Operational and Transportation Costs by Hamed Nozari, Maryam Rahmaty, Parvaneh Zeraati Foukolaei, Hossien Movahed, Mahmonir Bayanati

“…This paper discusses the modeling and solution of a cold chain logistics (CCL) problem using artificial intelligence of things (AIoT). …”
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Static Voltage Stability Evaluation and Correction Strategy Based on Stage Solving Strategy and SIFT by Yan Wen, Xiaoming Liu, Yongzhi Zhou, Huiwen Zhang, Donglei Sun

“…Aiming at the static voltage instability problem of the power grid caused by large-scale access of renewable energy sources, the study adopts the scale invariant feature transform algorithm for boundary feature extraction, while optimizing the traditional generalized resilience index of the power grid. …”
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Simulation and reconstruction of parameters of streamflow and glacier mass balance in the Northern Caucasus by V. G. Konovalov

“…And for this data we study a relationship with meteorological parameters which are measured at a non-regular observational network whose spatial representativeness is unknown. …”
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Municipal solid waste supply chain optimization for value-added product development under uncertainty by Muazzam Mukhtar, Muhammad Rizwan, Atta Ullah, Ali Elkamel, Salman Raza Naqvi, Muhammad Zaman

“…This study focuses on addressing the MSW supply chain problem by exploring the optimal location for the waste treatment. …”
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RETRACTED ARTICLE: Machine learning intelligent based hydromagnetic thermal transport under Soret and Dufour effects in convergent/divergent channels: a hybrid evolutionary numeric... by Muhammad Naeem Aslam, Nadeem Shaukat, Arshad Riaz, Ilyas Khan, Shafiullah Niazai

“…We utilized artificial neural networks (ANNs) to investigation the dynamics of the problem. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…This paper addresses the problem of accurate energy forecasting by proposing an intelligent hybrid model that integrates advanced feature selection, signal decomposition, and deep learning techniques. …”
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Analysis and Research on Intelligent Logistics Data under Internet of Things and Blockchain by Yige Li

“…It can effectively solve the traceability problem of logistics transaction information, and the calculation cost is stable within 1,000 ms. …”
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Identification of glass eel capture equipment in the Yangtze River estuary based on high-spatial -resolution imagery and an improved YOLOv8 model by Pengfei Zhu, Weifeng Zhou

“…Then, C2f module was improved with dual convolutional kernels, and the pooling process was improved by introducing the spatial pyramid pooling fast module with enhanced local attention network. Thereupon the detection speed and accuracy are both improved. …”
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Synergistic effect of artificial intelligence and new real-time disassembly sensors: Overcoming limitations and expanding application scope by Bozhou Li, Dajiang Ju, Xingwang Li, Yan Liu, Hongru He, Hao Wang

“…Then, based on the gated recurrent unit (GRU) model, the article applied the particle swarm optimization (PSO) algorithm to optimize the parameters of the GRU network and used the support vector machine (SVM) model to optimize the classification function of the network output. …”
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Multi-layer perceptron-particle swarm optimization: A lightweight optimization algorithm for the model predictive control local planner by Xiaoqing Guan, Tao Hu, Ziang Zhang, Yixu Wang, Yifan Liu, You Wang, Jie Hao, Guang Li

“…Next, to accomplish obstacle avoidance, the particle swarm optimization algorithm re-optimizes the trajectory based on the outputs of the neural network. The experiment results demonstrate that the multi-layer perceptron-particle swarm optimization algorithm can quickly and accurately solve local planning problems, guiding robots to complete global paths with the same efficiency as expert solvers. …”
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DCP-YOLOv7x: improved pest detection method for low-quality cotton image by Yukun Ma, Yajun Wei, Minsheng Ma, Zhilong Ning, Minghui Qiao, Uchechukwu Awada

“…This paper proposes a low-light environments cotton pest detection method, DCP-YOLOv7x, based on YOLOv7x, to address the issues of degraded image quality, difficult feature extraction, and low detection precision of cotton pests in low-light environments.MethodsThe DCP-YOLOv7x method first enhances low-quality cotton pest images using FFDNet (Fast and Flexible Denoising Convolutional Neural Network) and the EnlightenGAN low-light image enhancement network. …”
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Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. by Qi Jin

“…Facing the current problems of high data transmission delay, low efficiency, and large task volume in the electric power IoT, this research combines software-defined networking to design a multi-path low-latency routing and transmission model under the concept of task allocation. …”
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Minimizing Age of Information in Slotted ALOHA With Short-Packet Communications by Yoora Kim

“…In this paper, we address the problem of minimizing AoI in short-packet SA networks where multiple devices transmit their time-stamped status packets to a common access point. …”
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Document Relevance Filtering by Natural Language Processing and Machine Learning: A Multidisciplinary Case Study of Patents by Raj Bridgelall

“…These models include extreme gradient boosting, random forest, and support vector machines; a deep artificial neural network; and three natural language processing methods: latent Dirichlet allocation, non-negative matrix factorization, and k-means clustering of a manifold-learned reduced feature dimension. …”
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Enhancing microgrid performance: Optimal proactive reactive power dispatch using photovoltaic active power forecasts by Alexander Casilimas‐Peña, Karol Rosen, César Angeles‐Camacho

“…The proposed technique is evaluated in a CIGRE test network, showing an average loss reduction between 14% and 66% for sunny and cloudy conditions with different levels of PV penetration, this while maintaining the steady state voltages in range.…”
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An intelligent partial charging navigation strategy for electric vehicles by Jinsheng Xiao, Bang Sun, Xun Gao, Hua Yang, Liyuan Wang

“…The rise of electric vehicles (EVs) has highlighted the issue of insufficient charging infrastructure, a major barrier to their widespread adoption. This problem is due to the limited capacity of existing charging networks and the performance constraints of EV batteries. …”
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A data-driven power consumption estimation algorithm of catenary for electrified railway by Wanqi Zhang, Shaobing Yang, Tingting He, Dylan Dah-Chuan Lu, Mingli Wu

“…The underdetermined issue of multi-train condition can be converted into a problem within a finite solution domain, depending on either the average speed, speed limit, or both. …”
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Intelligent library shelf management system for open-access environments: A CNN-based approach with enhanced image recognition and disorder detection by Xueqi Zhang

“…Experimental results demonstrated that the improved algorithm exhibited superior performance to convolutional neural networks and support vector machine algorithms. The accuracy increased by 2.11% and 4.76%, the root mean square error decreased by 0.12 and 0.21, and the average percentage error decreased by 0.14 and 0.28, respectively. …”
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Efficiency Calculation and Analysis of Green Economy Based on Improved Fixed Effects Model by Kaige Liu, Ze Fu, Yuxi Chai

“…The discrepancy between global economic growth and environmental degradation has become increasingly pronounced, and the calculation of green economic efficiency has become a key issue. In response to the problem of traditional fixed effects models neglecting important heterogeneity factors in measuring green economic efficiency, this study proposes an improved fixed effects model combined with long short-term memory neural network classification algorithm. …”
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