Evaluation Of Efficiency Research Articles

Multi-objective optimization of airfoils with integral tubular high-pressure tanks for hydrogen storage

Reducing the environmental impact of air transport is one of today's most important challenges in aviation industry and research. A promising key enabler is the use of hydrogen as an alternative to fossil fuels. The development of hydrogen-powered aircraft poses new engineering challenges due to its low volumetric energy density requiring high-pressure or cryogenic storage. If the volume in the wing shall be further used for storing hydrogen under high pressure, new demands arise to airfoil design. The present work focuses on this issue by presenting a multi-objective optimization approach aiming for airfoils with both low drag and high volume for internal tubular high-pressure tanks. This allows to directly address the new design objective and to find novel airfoil shapes providing the best compromise between aerodynamic efficiency and high storage volume for pressurized hydrogen. The resulting optimization problem is solved using Evolutionary Algorithms. For an efficient aerodynamic evaluation, the open source viscous-inviscid panel method XFOIL is used. An application example, based on the flight conditions of a general aviation aircraft, demonstrates the applicability of the method. Comparisons of the resulting aerodynamic characteristics obtained by XFOIL with RANS simulations confirm the feasibility of the results.

Synthesis And Efficiency Evaluation of Chitosan-Alginate Hydrogel Polyelectrolyte Complex Filter for Treatment of Oil Spillage

Crude oil spills pose considerable environmental concerns thereby demanding the development of effective, sustainable, and eco-friendly remediation solutions. In this study, we synthesized and evaluated the efficiency of a biodegradable polymer filter using sodium alginate and chitosan for the treatment of oil spillage. The sodium alginate-chitosan hydrogel polyelectrolyte complex (SACHPC) filter was synthesized via dipping method using a layer-by-layer self-assembly technique integrated with cotton wool as the filter medium. The efficiency of the filter was evaluated based on flow rate of recovered oil and reusability of the filter. Simulated oil spillage of 0.5 M was subjected to filtration using the SACHPC filter. The flow rate was determined based on the time taken for 1 L of oil to pass through the filter. The SACHPC filter exhibited underwater superoleophobic behaviour with exceptional filtration efficiency (> 98.3%) in acidic, neutral and alkaline conditions (pH 3, 7 and 11). The flow rate of the filter was 120 mL/min, while the third-use filter exhibited a decrease flow rate of 50 ml/min. Moreover, the filter achieved an impressive crude oil recovery rate of 85%. X-ray diffraction analysis confirmed crude oil adsorption in the presence of an amorphous phase while scanning electron microscopy analysis revealed the structural morphology of the SACPHC filter. Overall, the SACHPC filter maintained high filtration efficiency thereby offering a sustainable strategy for oily wastewater purification and oil spill clean-up.

Evaluation of heat transfer enhancement effect at the hot/cold end of a Stirling engine using performance improvement factor

The driving force of a Stirling engine comes from the heating expansion and cooling compression of working medium. The enhancement of heat transfer capacity of the hot/cold end is the key to improve the Stirling engine performance, while how to objectively evaluate the heat transfer enhancement effect is a precondition. Herein, a polytropic model of a Stirling engine thermal cycle process was firstly established. A method for evaluating the heat transfer enhancement performance under oscillating flow was proposed based on the efficiency and power improvement of a Stirling engine. This method was further used to evaluate the heat transfer enhancement effect of a novel four-leaf helical heating tube under oscillating flow, the efficiency and power improvement factor of which was reached 13.5 % and 6.1 %, respectively. The results show that the efficiency and power improvement evaluation criterion was more comprehensive and intuitive in evaluating the heat transfer enhancement performance under oscillating flow compared with the conventional evaluation indictor like performance evaluation criterion and equivalent tube length and tube number criterion.

SIEMES DIGITAL TRANSFORMATION CASE STUDY TOWARDS ORGANIZATIONAL SCALE AND SUCCESS IN ELECTRICAL ENGINEERING INDUSTRY”

This study investigates a range of scaling strategies for electrical engineering firms, with a focus on various crucial aspects such as internal innovation, strategic regional expansion, geographical proximity, and collaborative partnerships. Internal innovation is highlighted as a key driver of growth, as it allows firms to develop new technologies and processes that can differentiate them from competitors. Strategic regional expansion is discussed as a means to tap into new markets and leverage local opportunities, while geographical proximity is examined for its impact on operational efficiency and customer relationships. Collaborative partnerships are also emphasized for their role in enhancing capabilities and driving mutual benefits. The case study of Siemens AG serves as a prominent example, showcasing how digital technologies like the Internet of Things (IoT), artificial intelligence (AI), and cloud computing have significantly transformed their approach to scaling. Siemens AG's experience underscores how these technologies can support internal innovation, streamline regional expansion efforts, overcome geographical barriers, and foster effective collaborations. The article proposes a detailed framework in which digital transformation is central to driving these strategies. It argues that digital technologies are not just enablers but essential components that fuel innovation across various domains. Additionally, digital transformation is posited as a critical factor in facilitating smoother and more effective expansion into new regions, bridging geographical gaps that can otherwise impede growth, and enhancing collaborative efforts both within and outside the organization. By integrating these elements, businesses can achieve sustainable growth and maintain a competitive edge in an ever-evolving and challenging market landscape.is considered near the evaluation of efficiency of management an enterprise. Evaluation technology is realized on the basis of comparison of financial indexes, in particular to the analysis of indexes of profitability and analysis of business activity

Analysis of knowledge services efficiency and influencing factors of public libraries in China: a mixed study based on the SBM model and dynamic QCA

PurposeThe core objective of this study is to provide an in-depth quantitative assessment of the efficiency of public library knowledge services (PLKS) in China and to scrutinize the factors that have a significant impact on the efficiency of PLKS. Furthermore, this study also aims to examine the characteristics and evolving patterns of PLKS in China and to propose strategies for enhancing the quality of services provided by public libraries. The findings of this paper are expected to provide valuable references for current academic research and practice areas, guiding and promoting exploration and development in related fields.Design/methodology/approachTo analyse and evaluate the operation mechanism and efficiency of PLKS, this study creatively constructs a multi-stage PLKS efficiency evaluation model and provides related indicators. Based on this process, the super-efficiency network slacks-based measure model was used to analyse the efficiency, and dynamic qualitative comparative analysis was adopted to analyse the recipes about the influencing factors of PLKS. Ultimately, through a comprehensive interpretation of the measured data and the integration of extant societal development conditions, the authors put forth relevant recommendations.FindingsIn the first stage, PLKS in China meets the basic requirements, but in the second stage, there is evident resource wastage. In addition, there are five recipes in PLKS of China. These five recipes reveal the configuration relationship between the factors that affect PLKS. The results show that PLKS in China are different in different regions, and the effects of the influencing factors are also different.Originality/valueIn this study, the authors provide an exhaustive deconstruction and interpretation of PLKS, thereby proposing a three-stage PLKS efficiency conversion process. Furthermore, the authors have identified a set of readily accessible and quantifiable indicators. It is worth emphasizing that the authors have taken a unique approach to analyse the elements affecting PLKS from the perspective of configuration, which has significantly broadened the boundaries and depth of PLKS research.

Simplification and simulation of evaluation process for low efficiency constructed wetlands based on principal component analysis and machine learning

The existing performance evaluation process of constructed wetlands (CWs) is complex, with shortcomings in both simplification of method and construction of simulation model, especially for low-efficiency CWs (LECWs, with an average close-degree calculated by the entropy weight method being <0.6). This study presents a case study of LECWs in the Ningxia region (comprising 13 subsurface flow constructed wetlands (SSF CWs) and 7 surface flow constructed wetlands (SF CWs)), employs the entropy weight method (EWM) to construct an evaluation of CW operational efficiency, simplifies evaluation indicators through principal component analysis (PCA), develops two random forest (RF) models to validate the rationality of the simplified indicators, and establishes simulation models by logistic regression (LR). The results demonstrate that the evaluation indicators of CWs can be simplified to chemical oxygen demand (COD) and total nitrogen (TN), with no significant difference observed between the evaluation results and the original model (P < 0.05), thereby indicating reliability. Moreover, the simulation model performs well with R2 values for fitting SSF CWs and SF CWs exceeding 0.8. According to the simulated results of the model, the operational efficiency of LECWs is more significantly affected by the COD removal rates compared to the TN removal rates. In comparison to influent with 0 < COD/TN < 3 and 5 < COD/TN < 8, the operational efficiency of SSF CWs and SF CWs is optimal when COD/TN is between 3 and 5. These research findings may provide valuable support for streamlining evaluation processes and daily management for LECWs.

Of the article: evaluation of the masticatory efficiency of children with stainless steel crowns: a pilot cross-sectional split-mouth study

BackgroundStainless steel crowns (SSCs) are commonly employed to restore the posterior teeth of children and over the years, they are available with improved anatomical shapes. This study was conducted to evaluate and assess the effect of the placement of SSCs on the masticatory efficiency of children.MethodsThis pilot cross-sectional split-mouth study assessed masticatory efficiency in children aged 6–11 years. Fifteen participants, each with stainless-steel crowns placed unilaterally at least one month prior, were included. This study utilized two flavours of trident chewing gum (red and green) to measure masticatory efficiency. The child was asked to chew half a strip of red and green chewing gum placed one on top of the other using either the noncrown or crown side 15 times. Another set of chewing gum was given to the child to chew 20 times on the same side. The chewing exercise was repeated using teeth on the other side. Chewed gum samples were collected, photographed, and analysed via ImageJ software to determine the red and green areas. Masticatory efficiency was subsequently calculated with the help of a formula in which the red areas and green areas were calculated via ImageJ software. The data were analysed with paired t tests via SPSS (version 20.0).ResultsWhen the mean values of the crown side were compared with those of the noncrown side following 15 chewing cycles, the chewing efficiency on the noncrown side was greater, with a difference of 0.303, whereas the chewing efficiency following 20 chewing cycles was greater on the crown side, with a difference of 0.814. However, both differences were statistically nonsignificant, with t values of -0.07 and 0.26, respectively, and p values of 0.94 and 0.8, respectively.ConclusionThe presence of SSCs on the molars of children did not affect masticatory efficiency.

Study on The Areal Sweep Efficiency and Water Breakthrough Time Prediction of Water Flooding in Carbonate Reservoirs

Abstract This study concentrates on the evaluation of areal sweep efficiency and the prediction of water breakthrough time in a representative medium-porosity, medium-high permeability thin carbonate reservoir, using the H oilfield in the Middle East as an example. Areal geological models, accounting for variations in high permeability streaks and regional heterogeneity, were established to study the impact of areal heterogeneity on the sweep coefficient and morphology of the water flooding front. The results revealed that areal heterogeneity significantly affects both the areal sweep efficiency and the morphology of the water flooding front. In models with high permeability streaks, a greater permeability ratio led to more uneven displacement in all directions, consequently, this resulted in a poorer overall development effect. Furthermore, regional heterogeneity was found to significantly impact sweep efficiency, the larger the area of relatively low permeability zones, the more severe the reduction in sweep efficiency and the overall injection production effect. A theoretical method for accurately predicting water breakthrough time was established based on the stream tube method. This method was applied to the H oilfield, which reduced the discrepancy between the predicted and actual breakthrough times, thereby confirming its feasibility. The novelty of this study lies in overcoming the limitations of the stream tube method and utilizing numerical simulation to calculate the areal sweep coefficient at the time of water breakthrough. This approach quantitatively characterized the affected streamline area, thereby enhancing the accuracy of water breakthrough time predictions. This research provides significant theoretical insights and practical references for understanding the areal sweep efficiency of thin carbonate reservoirs, predicting water breakthrough times, and optimizing injection production strategies.

Quantitative analysis of transferrin uptake into living cells at single-molecule level

Endocytosis, apart from providing a mechanism for cells to take up nutrients, is the principal route of entry for many nanomedicines. The evaluation of therapeutic delivery efficiency without providing quantitative parameters, like the number of molecules entering the cell and the time of their entry, is very limited. Despite advances in single-molecule methods for in-cell quantitative measurements, they have not become widely used in the study of endocytosis. Their application, however, is challenging owing to the appropriate experimental design and applicable analysis methods. Here, by using an integrated approach based on the multidimensional time-correlated single-photon counting (TCSPC) technique, we demonstrate the quantitative method to measure the time- and concentration-dependent uptake of TRITC-transferrin into living cells with single-molecule sensitivity. The methodology opens possibilities for quantitatively assessing the delivery efficiency of fluorescent molecules into living cells.

Modern Methods of Evaluating the Efficiency of Logistics Processes in a Company

The article discusses modern methods of assessing the efficiency of logistics processes, which are one of the most important components of the successful functioning of any company, especially in today's fierce competition and globalization. The article assesses the efficiency of logistics processes, which are an integral part of the company's strategic management and allow ensuring its stable development. The analysis of modern methods for assessing the efficiency of logistics processes in a company has allowed to identify three important tools, such as: data envelopment analysis (DEA), ABC analysis and cost analysis and control method. It is proved that the DEA method can be applied to a wide range of logistics systems, regardless of their complexity and specificity. In addition, DEA allows to identify factors that limit efficiency and develops recommendations for its improvement. The value of ABC analysis is highlighted, which lies in the potential to increase sales volumes by improving the availability of goods that are most valued by customers. An assessment of the efficiency of logistics processes in a company using ABC analysis is proposed. The importance of such a method as cost analysis and control is analyzed. Thanks to a detailed analysis and control of costs, it is possible to identify bottlenecks in the logistics chain, optimize delivery routes, reduce storage costs and increase the efficiency of vehicle use. The author proposes the key stages of the logistics cost analysis based on the “Five Steps” system. It is proved that the joint use of the proposed methods creates synergy, allowing for a deeper and more accurate analysis than when each of them is applied separately. The methods we have studied complement each other, providing company managers with tools for comprehensive analysis and evaluation of logistics efficiency.

A novel configuration optimization approach for IES considering exergy-degradation and non-energy costs of equipment

Improving the exergy utilization and economic performance is the core goal for the configuration optimization of the integrated energy system (IES). Achieving such a goal requires accurate evaluation of the exergy efficiency and economy. However, IES is a multisource heterogeneous and strongly coupled system. The development of reasonable exergy efficiency-economy characteristic evaluation indicators is a complex issue that limits its application in IES configuration. This article proposes a novel IES configuration optimization approach based on the concept of the equipment exergyeconomic cost coefficient. The exergyeconomic cost coefficient consists of the exergy-degradation and non-energy costs, which can quantitatively characterize the exergy efficiency and economy of the IES under a unified benchmark. A mechanism model for the equipment exergyeconomic cost coefficient, output of various equipment and total exergyeconomic cost is established. Furthermore, exergy flow attribute classification method is proposed to obtain the equipment exergyeconomic cost coefficient in the IES. The proposed method is verified in a real-world study case located in Yancheng, China. Compared to the conventional configuration method, the capacity of the renewable energy and combined heat and power generation (CHP) are enhanced, while the capacity of purchased electricity and electric boiler (EB) are reduced. It can obtain the minimum total exergyeconomic cost (TEC) for the IES. This study offers a new direction for the optimal configuration of IES.

Assessing economic efficiency of driving behavior within traffic flow dynamics

The widespread adoption of electric vehicles has a positive impact on energy conservation and emission reduction, significantly contributing to sustainable development. This paper proposes an economic evaluation method for drivers’ driving behaviors based on actual operational data of pure electric vehicles. This method aims to eliminate the influence of traffic conditions on the evaluation results, ensuring that the outcomes solely reflect the economic efficiency level of drivers’ behaviors. Initially, short trips are identified and traffic conditions are classified and identified based on real vehicle data. A random forest identification model is established to recognize the traffic conditions of short trips in real-time. Subsequently, characteristic variables are selected and calculated. Pearson correlation analysis wand Spearman correlation analysis are utilized to identify variables strongly correlated with energy consumption and traffic conditions, which are then used as evaluation indicators. Finally, eco-scores are calculated using the energy consumption per unit mileage for short trip segments under different traffic conditions. A neural network model is established and trained between the evaluation indicators and eco-scores, enabling real-time evaluation of the economic efficiency of drivers’ driving behaviors. The evaluation method proposed in this paper can objectively assess the economic efficiency of driving behavior, facilitating drivers to improve their driving practices based on their evaluation results.

Evaluation of the Aggregation Efficiency Modeling at Colder Atmospheric Temperatures in Comparison to Satellite Observations

Abstract Aggregation efficiency in the upper troposphere is highly uncertain because of the lack of laboratory experiments and aircraft measurements, especially at atmospheric temperatures below −30°C. Aggregation is physically broken down into collision and sticking. In this study, theory-based parameterizations for the collision efficiency and sticking efficiency are newly implemented into a double-moment bulk cloud microphysics scheme. Satellite observations of the global ice cloud distribution are used to evaluate the aggregation efficiency modeling. Sensitivity experiments of 9-day global simulations using a high-resolution climate model show that the use of collision efficiency parameterization causes a slight increase in the cloud ice amount above the freezing level over the tropics to midlatitudes and that the use of our new sticking efficiency parameterization causes a significant increase in the cloud ice amount and a slight decrease in the snow amount particularly in the upper troposphere over the tropics. The increase/decrease in the cloud ice/snow amount in the upper troposphere over the tropics is consistent with the vertical profile of radar echoes. Moreover, the ice fraction of the cloud optical thickness is still underestimated worldwide. Finally, the cloud radiative forcing increases over the tropics to reduce the bias in the radiation budget. These results indicate that our new aggregation efficiency modeling reasonably functions even at atmospheric temperatures below −30°C; however, further improvements in the ice cloud modeling are needed. Significance Statement Long-standing biases in the radiative budget in climate models indicate the existence of a missing mechanism to realistically represent the ice cloud growth in the upper troposphere. This study focuses on aggregation efficiency, which has been assumed to be a tuning parameter to optimize the global radiative budget. Therefore, this study employs a theory-based parameterization to calculate the aggregation efficiency. According to the parameterization, aggregation efficiency in high clouds varies by the growth stage of the individual ice particles. As a result, small ice crystals are likely to grow more slowly, and the lifetime of cirrus clouds is prolonged to enhance cloud radiative forcing, particularly over the tropics. These results are promising for reducing the biases observed in climate models.

Evaluation and convergence analysis of science and technology innovation efficiency in China’s national central cities based on the super-efficiency SBM-ML model

ABSTRACT Scientific and Technological Innovation (STI) is an important driving force for economic development and social progress. National central cities are the main connection points of China’s economic activity network and play a leading role in the national economic development of the country. In order to explore the efficiency of STI and the convergence characteristics of STI in China’s national central cities, this paper selects S&T innovation input-output indicators and constructs a system of indicators for high-quality economic development. It measures the STI innovation efficiency of China’s national central cities by combining with the super-efficiency SBM-ML model and then constructs a model to analyze its convergence situation. The results of the study show that: from 2011 to 2021, the STI efficiency of China’s national central cities has reached an effective level, and the overall trend has increased; the total factor productivity of STI in China’s national central cities has obvious differences, with Beijing having the highest total factor productivity, while Shanghai has the lowest; the STI innovation efficiency of China’s national central cities exhibits both absolute β-convergence and conditional β-convergence, but there is no significant α convergence, and regional differences are obvious.

Design of optical performance for self-luminous pavement materials

The lower visibility in the nighttime environment makes higher accident risks during driving. Using self-luminous materials in pavement construction can effectively improve the luminance of load surface, thus significantly improve nighttime driving safety. This study has designed three types of self-luminous pavement materials (SLPM) with different optical properties by incorporating long-persistent luminescent aggregates into the mixture and using polymer binders with varying degrees of light transmittance, such as transparent polyurethane, transparent asphalt, and traditional asphalt. On this basis, utilizing digital image processing techniques to compare the optical performance differences among these three SLPM and established corresponding computational models based on the obtained data to enable efficient and accurate evaluation of the optical properties of pavement materials. The experimental results indicate that the durability performance of SLPM gradually diminishes over time, and this degree of attenuation is negatively correlated with the light transmittance of the binder. Specifically, a higher light transmittance of the binder results in a smaller decline in SLPM durability, whereas a lower transmittance leads to a more significant reduction. The optical performance calculation model established by this research can predict the reflective performance of SLPM through the optical parameters of aggregate, binders, and the doping amount of long persistent luminescent materials. In addition, the model can accurately calculate the minimum content of self-luminous materials according to the optical requirements required by the project, which can provide a reference for the performance evaluation of self-luminous pavement materials and the selection of optimal proportioning scheme.

Chemical profile of compounds in irrigated arabica coffee by ESI-MS

The use of irrigation in coffee aims productivity increase and better quality of the final product. The impacts of irrigation in productivity and quality are impressive. In this study, ten different varieties of Coffea arabica L., were cultivated with irrigation and no irrigation regimes and these samples were analyzed by direct infusion electrospray ionization mass spectrometry (ESI-MS), in positive mode. The constituents identified were choline; trigonelline; sucrose; βN-arachinoyl-5-hidroxytryptamide; βN-behenoyl-5-hidroxytryptamide; palmitoyl-linoleoyl (PL); dilinoleoyl (LL); dipalmitoyl-linoleoyl (PPL); palmitoyl-dilinoleoyl (PLL) and three new compounds reported in coffee – triacylglycerol (TG 54:6), phosphoethanolamine (PE 40:7) and 1-hexadecyl-2-dodecanoyl-glycero-3-phosphate It was possible to efficiently sort the groups of irrigated and non-irrigated using PLS-DA to obtain all the minimum requirements for evaluation of efficiency of the rating model. Sucrose and the ion m/z 431 (not identified) suffered a negative influence of irrigation. The trigonelline, and the ion m/z 723 (not identified) were influenced positively by irrigation. The cup test showed that the coffees cultivated in not-irrigated regime had slightly larger cupping notes that the ones cultivated under irrigation, probably because they presented higher sucrose content.

Efficiency decomposition and frontier projection of two-stage network DEA under variable returns to scale

The efficiency decomposition and frontier projection of traditional two-stage network data envelopment analysis (DEA) model under variable returns to scale (VRS) are often not equivalent; which not only contradicts DEA theory, but also reduces the scientificity of the model. The main reason for this inequivalence is that there is a synergistic effect of variable scale return in two different stages. Therefore, this paper describes the production frontier of two-stage DEA under VRS for analyzing this synergistic effect, and then the efficiency evaluation pitfalls of two-stage DEA under VRS are identified. From the input orientation, output orientation, non-orientation perspectives, different two-stage network DEA models under VRS are respectively constructed to solve these evaluation pitfalls, and the equivalence relationships of their multiplier model and envelopment model are proved; and then the efficiency decomposition and frontier projection with equivalence relationship can be obtained to meet the different needs of decision-makers. Furthermore, variable intermediate element is discussed in the non-orientation model for achieving the Pareto optimality of two stages during the process of efficiency decomposition and frontier projection. By these models, the theoretical foundation of two-stage network DEA under VRS has been further improved. Finally, two examples are provided to illustrate the effectiveness of the new models.

Carbon sink efficiency of Chinese mollusk mariculture

Chinese mollusk mariculture plays a key role in boosting ocean carbon sink capacity through biological processes, supported by large-scale production. However, its full potential remains underutilized due to the absence of comprehensive efficiency evaluations. This interdisciplinary study applies a three-stage approach to assess the carbon sink efficiency of Chinese mollusk mariculture, with a focus on regional variations across nine coastal provinces from 2012 to 2022. The results show that environmental variables and statistical noise distort efficiency scores, leading to overestimation in six provinces and underestimation in three. After adjusting for these influences, regional disparities in efficiency become more apparent. High-production provinces such as Shandong, Fujian, and Guangdong exhibit higher efficiency, while low-production provinces like Hainan show diminished performance. Although there is a positive correlation between production volume and carbon sink efficiency, further improvements are constrained by the sector's low profitability. To address this, we propose two strategies: (1) reallocating subsidies from capture fisheries to mollusk mariculture, and (2) accelerating carbon trading between mollusk mariculture and other industries. These measures could enable the global mollusk mariculture to enhance both its carbon sink capacity and efficiency, contributing to food security and climate change mitigation.

Safety and Efficiency Evaluation of Carbon Dioxide Removal in Combination with Continuous Veno-Venous Hemodialysis/Hemodiafiltration Therapy: Baseline Characteristics of the multiECCO2R Study

Safety and Efficiency Evaluation of Carbon Dioxide Removal in Combination with Continuous Veno-Venous Hemodialysis/Hemodiafiltration Therapy: Baseline Characteristics of the multiECCO2R Study

Efficiency evaluation of electricity demand prediction models in lower-income countries: a case study of panama

Abstract Electricity plays a crucial role in the development of countries, serving as the foundation for the functioning of modern societies and as a key indicator of a nation’s level of modernization and overall strength. Predicting a country’s electricity demand provides valuable insights into the evolving patterns of electrical energy provision and usage and helps to improve the flexibility of the energy distribution network. In addition, it provides early warnings and decision support for governments, businesses, and individuals about future electricity consumption. This plays a pivotal function in optimizing power distribution, adjusting the proportion of power generation sources, and ensuring a continuous and secure electricity supply. This paper uses the example of electricity demand in Panama and uses the LSTM model and Prophet model to compare their predictions for electricity demand in lower-income countries, with the aim of improving accuracy. Furthermore, it introduces a data set representing the electricity demand of higher-income countries, using the United Kingdom as a representative, to compare the forecast results between the two countries. The results indicate that within the Panama data set, the Prophet model exhibits better accuracy than the LSTM model. On the contrary, in the data set representing higher-income countries with the United Kingdom as a representative, the LSTM model outperforms the Prophet model. This leads to the conclusion that the selection of a predictive model is specific to each country, influenced by factors such as development status, geographic location, policies, energy markets, and more. A specific model may not be universally applicable due to these unique conditions, requiring tailored-modeling approaches for precise and efficient allocation and scheduling of electricity resources. This approach ensures the improvement of residents’ living standards and quality of life while meeting the typical demands of a country’s economic and social development.