The Use and Abuse of Economics in Land Use Decision-Making in South Florida: An Industrial Park & Its Alternatives, 2020-2023

This paper reviews the economic methodology used to justify a proposed 357 hectare (800 acre) Industrial Park that would breach the Urban Development Boundary (UDB) in Miami-Dade County, Florida, a boundary that had been established to constrain urban sprawl and protect the surrounding wetlands and farmlands. We will examine the socio-economic setting of the region, the ownership of the farmland parcels designated to become industrial sites, and the misuse of the promoters’ narrow economic analysis. Then we shall explain and compute correctly the likely job creation based on the author’s own survey of recently constructed industrial plants similar to those proposed for this site. Rather than an industrial park, we offer instead a newly-designed multi-purpose Recreational–Ecological–Agricultural Park (REAP) & Nature Preserve which would maintain the integrity of the rural landscape, connect the densely-populated neighborhoods to the mangrove shoreline, and open nature’s treasure chest to urban Miami and the wider public.

Evolutionary Decision-Making and Planning for Autonomous Driving Based on Safe and Rational Exploration and Exploitation

Decision-making and motion planning are extremely important in autonomous driving to ensure safe driving in a real-world environment.This study proposes an online evolutionary decision-making and motion planning framework for autonomous driving based on a hybrid data-and model-driven method.First,a data-driven decision-making module based on deep reinforcement learning(DRL)is developed to pursue a rational driving performance as much as possible.Then,model predictive control(MPC)is employed to execute both longitudinal and lateral motion planning tasks.Multiple constraints are defined according to the vehicle’s physical limit to meet the driving task requirements.Finally,two principles of safety and rationality for the self-evolution of autonomous driving are proposed.A motion envelope is established and embedded into a rational exploration and exploitation scheme,which filters out unreasonable experiences by masking unsafe actions so as to collect high-quality training data for the DRL agent.Experiments with a high-fidelity vehicle model and MATLAB/Simulink co-simulation environment are conducted,and the results show that the proposed online-evolution framework is able to generate safer,more rational,and more efficient driving action in a real-world environment.

Understanding Urban Vitality from the Economic and Human Activities Perspective:A Case Study of Chongqing,China

The literature on urban vitality tends to focus on the built environment.This paper argues that some important processes in shaping vitality may be overlooked without examining the intensity and diversity of economic and human activities.Using newly developed spatial big data and adopting the methods of multi-indicator measurement and spatial analysis methods,we analyzed the pattern of urban vitality in Chongqing,a provincial city in western China and,on this basis,evaluated the creation and maintenance of urban vitality from the economic and human activities perspective.Our findings indicate that the impacts of economic and human activities are positive and significant.Among the three intensity and diversity indicators,economic intensity and population density show an effect on urban vitality stronger than that of economic diversity.However,economic diversity has the strongest superposition or interactive effect,and is thus an important foundation dynamic.The positive effect of population density on urban vitality is largely a result of Chongqing’s jobs-housing balance.The case of Chongqing highlights the importance of topographic features,historical inheritance,large-scale migration,and cultural activities in shaping the distinctive vitality pattern of a city.This study contends that the creation and maintenance of urban vitality can not be fully explained without incorporating the impacts of economic and human activities.It contributes to a comprehensive measurement of urban vitality and enriches its connotations.

Toward Trustworthy Decision-Making for Autonomous Vehicles:A Robust Reinforcement Learning Approach with Safety Guarantees

While autonomous vehicles are vital components of intelligent transportation systems,ensuring the trustworthiness of decision-making remains a substantial challenge in realizing autonomous driving.Therefore,we present a novel robust reinforcement learning approach with safety guarantees to attain trustworthy decision-making for autonomous vehicles.The proposed technique ensures decision trustworthiness in terms of policy robustness and collision safety.Specifically,an adversary model is learned online to simulate the worst-case uncertainty by approximating the optimal adversarial perturbations on the observed states and environmental dynamics.In addition,an adversarial robust actor-critic algorithm is developed to enable the agent to learn robust policies against perturbations in observations and dynamics.Moreover,we devise a safety mask to guarantee the collision safety of the autonomous driving agent during both the training and testing processes using an interpretable knowledge model known as the Responsibility-Sensitive Safety Model.Finally,the proposed approach is evaluated through both simulations and experiments.These results indicate that the autonomous driving agent can make trustworthy decisions and drastically reduce the number of collisions through robust safety policies.

Orientation and Decision-Making for Soccer Based on Sports Analytics and AI:A Systematic Review

Due to ever-growing soccer data collection approaches and progressing artificial intelligence(AI) methods, soccer analysis, evaluation, and decision-making have received increasing interest from not only the professional sports analytics realm but also the academic AI research community. AI brings gamechanging approaches for soccer analytics where soccer has been a typical benchmark for AI research. The combination has been an emerging topic. In this paper, soccer match analytics are taken as a complete observation-orientation-decision-action(OODA) loop.In addition, as in AI frameworks such as that for reinforcement learning, interacting with a virtual environment enables an evolving model. Therefore, both soccer analytics in the real world and virtual domains are discussed. With the intersection of the OODA loop and the real-virtual domains, available soccer data, including event and tracking data, and diverse orientation and decisionmaking models for both real-world and virtual soccer matches are comprehensively reviewed. Finally, some promising directions in this interdisciplinary area are pointed out. It is claimed that paradigms for both professional sports analytics and AI research could be combined. Moreover, it is quite promising to bridge the gap between the real and virtual domains for soccer match analysis and decision-making.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Stroke Risk Assessment Decision-Making Using a Machine Learning Model:Logistic-AdaBoost

Stroke is a chronic cerebrovascular disease that carries a high risk.Stroke risk assessment is of great significance in preventing,reversing and reducing the spread and the health hazards caused by stroke.Aiming to objectively predict and identify strokes,this paper proposes a new stroke risk assessment decision-making model named Logistic-AdaBoost(Logistic-AB)based on machine learning.First,the categorical boosting(CatBoost)method is used to perform feature selection for all features of stroke,and 8 main features are selected to form a new index evaluation system to predict the risk of stroke.Second,the borderline synthetic minority oversampling technique(SMOTE)algorithm is applied to transform the unbalanced stroke dataset into a balanced dataset.Finally,the stroke risk assessment decision-makingmodel Logistic-AB is constructed,and the overall prediction performance of this new model is evaluated by comparing it with ten other similar models.The comparison results show that the new model proposed in this paper performs better than the two single algorithms(logistic regression and AdaBoost)on the four indicators of recall,precision,F1 score,and accuracy,and the overall performance of the proposed model is better than that of common machine learning algorithms.The Logistic-AB model presented in this paper can more accurately predict patients’stroke risk.

Economic Stress, Precariousness and Risk of High Blood Pressure: A Descriptive Survey of Life Models within Households of the Central Region of Cameroon

Context/Objective: High blood pressure (HBP) currently represents the most widespread chronic non-communicable disease in Cameroon. The increase in its prevalence in the country is the result of multiple factors including economic stress imposed by precariousness, poor living conditions, sources of anxiety, anguish, depression and other behavioral disorders. Economic stress is a globalizing concept that integrates into a purely hermeneutic approach, a particular functioning of the nervous system of an individual who faces employment problems and precarious remuneration conditions. The non-satisfaction by an individual of his basic needs due to insufficient financial means can cause him to become irritable, aggressive, and socially and symbolically isolated, thereby increasing the desire to resort to morbid life models such as excessive consumption of narcotics and other psychoactive substances often associated with high blood pressure. The fight against the emergence of BPH is a complex, multifaceted and multifactorial reality that requires taking into account economic stress. The main objective of this survey is to describe the situation of economic stress within the Cameroonian population, which imposes precariousness and life models at risk of high blood pressure. Specifically, we determined the level of household income and the sources of income. Methods: A cross-sectional survey with a descriptive aim among five hundred households in the Central Region of Cameroon was conducted. A probabilistic technique called simple randomness was used. The number of households to be surveyed was determined indirectly using the Cochrane formula. Data collection in face-to-face mode using a physical questionnaire took place from July 1 to August 31, 2023, after obtaining ethical clearance from the Regional Health Research Ethics Committee, Human from the Center and an administrative authorization for data collection. Regarding their processing, the data was grouped during processing in Excel sheets. Normality and reliability tests of the collected data were carried out. For this, the Chi-square test was used for data with a qualitative value and that of Kolmogorov-Sminorf for data with a quantitative value. Descriptive analysis was possible using R software version 3.2, SPSS version 25.0, XLSTAT 2016, PAST and EXCEL programs from Microsoft Office 2013. Results: The main results highlight economic stress, with 45.60% of households surveyed earning less than US$154 per month;55% of household heads were women in single-parent families;14% of household heads were unemployed, 22% worked in the private sector and 19% were self-employed. This general economic situation leads to precarious living conditions, thereby increasing the risk of high blood pressure among the Cameroonian population.

Spatiotemporal pattern of climate change in the China-Myanmar Economic Corridor from 1901 to 2018

The China-Myanmar Economic Corridor(CMEC) is an important part of China's Belt and Road Initiative and an important area for global ecology and biodiversity. In this study, the annual and seasonal spatiotemporal patterns of temperature and precipitation in the CMEC over the past century were investigated using linear tendency estimation, the Mann-Kendall mutation test, the T-test, and wavelet analysis based on the monthly mean climatic data from 1901 to 2018 released by the Climatic Research Unit(CRU) of the University of East Anglia, UK. The results show that the CMEC demonstrated a trend of warming and drying over the past 100 years, and the rate of change in Myanmar was stronger than that in Yunnan Province of China. The warming rate was 0.039 ℃/10a. Precipitation decreased at a rate of -6.1 mm/10a. From the perspective of spatial distribution, temperature was high in the central and southern, low in the north of the CMEC, and the high-temperature centers were mainly distributed in the southern plain and river valley. Precipitation decreased from west to east and from south to north of the CMEC. From the perspective of the rate of change, warming was stronger in central and northern CMEC than in southern and northeastern CMEC. The rate of precipitation decline was stronger in the central and western regions than in the eastern region. This study provides a scientific reference for the CMEC to address climate change and ensure sustainable social and economic development and ecological security.

The Spherical q-Linear Diophantine Fuzzy Multiple-Criteria Group Decision-Making Based on Differential Measure

Spherical q-linearDiophantine fuzzy sets(Sq-LDFSs)provedmore effective for handling uncertainty and vagueness in multi-criteria decision-making(MADM).It does not only cover the data in two variable parameters but is also beneficial for three parametric data.By Pythagorean fuzzy sets,the difference is calculated only between two parameters(membership and non-membership).According to human thoughts,fuzzy data can be found in three parameters(membership uncertainty,and non-membership).So,to make a compromise decision,comparing Sq-LDFSs is essential.Existing measures of different fuzzy sets do,however,can have several flaws that can lead to counterintuitive results.For instance,they treat any increase or decrease in the membership degree as the same as the non-membership degree because the uncertainty does not change,even though each parameter has a different implication.In the Sq-LDFSs comparison,this research develops the differentialmeasure(DFM).Themain goal of the DFM is to cover the unfair arguments that come from treating different types of FSs opposing criteria equally.Due to their relative positions in the attribute space and the similarity of their membership and non-membership degrees,two Sq-LDFSs formthis preference connectionwhen the uncertainty remains same in both sets.According to the degree of superiority or inferiority,two Sq-LDFSs are shown as identical,equivalent,superior,or inferior over one another.The suggested DFM’s fundamental characteristics are provided.Based on the newly developed DFM,a unique approach tomultiple criterion group decision-making is offered.Our suggestedmethod verifies the novel way of calculating the expert weights for Sq-LDFSS as in PFSs.Our proposed technique in three parameters is applied to evaluate solid-state drives and choose the optimum photovoltaic cell in two applications by taking uncertainty parameter zero.The method’s applicability and validity shown by the findings are contrasted with those obtained using various other existing approaches.To assess its stability and usefulness,a sensitivity analysis is done.

Economic Resilience in Bangladesh: Analyzing Household Well-Being amidst Price Hikes through ANOVA and Paired Sample t-Test Insights

This study delves into the multifaceted impact of price hikes on the standard of living in Bangladesh, with a specific focus on distinct socioeconomic segments. Amidst Bangladesh’s economic growth, the challenges of rising inflation and increased living costs have become pressing concerns. Employing a mixed-methods approach combines quantitative data from a structured survey with qualitative insights from in-depth interviews and focused group discussions to analyze the repercussions of price hikes. Stratified random sampling ensures representation across affluent, middle-class, and economically disadvantaged groups. Utilizing data [1] from 2020 to November 2023 on the yearly change in retail prices of essential commodities, analysis reveals significant demographic shifts, occupational changes, and altered asset ownership patterns among households. The vulnerable population, including daily wage laborers and low-income individuals, is disproportionately affected by adjustments in consumption, income generation, and living arrangements. Statistical analyses, including One-Way ANOVA and Paired Sample t-tests, illuminate significant mean differences in strategies employed during price hikes. Despite challenges, the prioritization of education remains evident, emphasizing its resilience in the face of economic hardships. The result shows that price hikes, especially in essential items, lead to substantial adjustments in living costs, with items like onions, garlic, and ginger experiencing significant increases of 275%, 108%, and 483%, respectively.

A NovelMethod for Determining Tourism Carrying Capacity in a Decision-Making Context Using q−Rung Orthopair Fuzzy Hypersoft Environment

Tourism is a popular activity that allows individuals to escape their daily routines and explore new destinations for various reasons,including leisure,pleasure,or business.A recent study has proposed a unique mathematical concept called a q−Rung orthopair fuzzy hypersoft set(q−ROFHS)to enhance the formal representation of human thought processes and evaluate tourism carrying capacity.This approach can capture the imprecision and ambiguity often present in human perception.With the advanced mathematical tools in this field,the study has also incorporated the Einstein aggregation operator and score function into the q−ROFHS values to supportmultiattribute decision-making algorithms.By implementing this technique,effective plans can be developed for social and economic development while avoiding detrimental effects such as overcrowding or environmental damage caused by tourism.A case study of selected tourism carrying capacity will demonstrate the proposed methodology.

UAV maneuvering decision-making algorithm based on deep reinforcement learning under the guidance of expert experience

Autonomous umanned aerial vehicle(UAV) manipulation is necessary for the defense department to execute tactical missions given by commanders in the future unmanned battlefield. A large amount of research has been devoted to improving the autonomous decision-making ability of UAV in an interactive environment, where finding the optimal maneuvering decisionmaking policy became one of the key issues for enabling the intelligence of UAV. In this paper, we propose a maneuvering decision-making algorithm for autonomous air-delivery based on deep reinforcement learning under the guidance of expert experience. Specifically, we refine the guidance towards area and guidance towards specific point tasks for the air-delivery process based on the traditional air-to-surface fire control methods.Moreover, we construct the UAV maneuvering decision-making model based on Markov decision processes(MDPs). Specifically, we present a reward shaping method for the guidance towards area and guidance towards specific point tasks using potential-based function and expert-guided advice. The proposed algorithm could accelerate the convergence of the maneuvering decision-making policy and increase the stability of the policy in terms of the output during the later stage of training process. The effectiveness of the proposed maneuvering decision-making policy is illustrated by the curves of training parameters and extensive experimental results for testing the trained policy.

Effects of Enclosure on Grassland Ecological and Economic Benefits in Northern China

Grasslands in northern China serve the country as both an ecological barrier and a livestock production base.There,installing enclosures has been becoming the major grassland restoration measure adopted by many local governments.However,the effects of restoration on both ecological and production benefits of grassland remain unclear for implemented grassland restoration policies.Therefore,a representative rangeland in northern China,the Maodeng pasture in Inner Mongolia Autonomous Region was selected as the study area,and remote sensing monitoring analyses were carried out to quantify the ecological benefits and economic benefits from 2015 to 2021.The results showed that:1) in terms of ecological benefits,the grassland area with a grassland coverage rate of more than 60% accounts for 32.3% of the regional area,and 86.4% of its grassland grew significantly better than the same period in2015,showing a significant improvement in grassland growth.Using the average amount of carbon per unit area as the ecological benefit evaluation index,it increased by 27.1% to 32.48Tg C/yr from 2015 to 2021.2) In terms of economic benefits,both theoretical grass production and livestock carrying capacity increased from 2015 to 2021.Compared to 2015,the theoretical grass production in 2021 increased by 24.8% to 71 900 t.The livestock carrying capacity reached 52 100 sheep units in 2021,nearly 11 000 sheep units more than that in 2015.During the study period,multiple economic indicators(on a per capita basis of permanent residents) for the pastoral area of Xilinhot City to which the Maodeng pasture belongs,have grown steadily.Per capita total income rose from 29 630 yuan(RMB) in2015 to 62 859 yuan(RMB) in 2021.Relying on grassland resources to develop the pastoral ecology also broadens the potential economic development space.Overall,the establishment of the reserve and the experiment of implanting an enclosure policy have had a significant and positive impact on Maodeng pasture’s development from both an ecological and economic perspective.With the support of scientific evidence,enclosure policy can be extended to more than 110 000 km~2 of grasslands in northern China with similar precipitation and temperature conditions,enhancing the productive and ecological potential of grasslands.The above research results will contribute to the scientific formulation of grassland pasture quality improvement plans in northern China.

Economic Growth Performance and Economic Activities in Kosovo During the Covid-19 Pandemic in Kosovo

The paper addresses economic growth and developments of economic activities during the Covid-19 crisis in Kosovo.After the last war,Kosovo continues to remain among the countries with a low level of development and a high rate of unemployment.The low level of economic growth and the high rate of unemployment remain among the main economic challenges for solution.The importance of the paper consists in addressing economic issues and processes including developments in economic activities during the Covid-19 crisis in Kosovo.Kosovo was affected by Pandemia Covid-19 starting from March 2020.Undoubtedly,the Covid-19 crisis has had effects on economic processes,affecting the activity of various sectors of the economy.The main purpose of this paper is to analyze the performance of economic growth and economic activities during the Covid-19 crisis in Kosovo.In order to achieve the objectives,the analysis method is mainly used,tabular and graphic separately,comparative method,analyzing in dynamics the issue related to economic activities in the Republic of Kosovo.Through this study,the results and recommendations given are considered to be considered by policy makers in the Republic of Kosovo.

Comprehensive evaluation and spatial-temporal evolution characteristics of urban resilience in Chengdu-Chongqing Economic Circle

To clarify the connotations and extensions of urban resilience,this study focuses on the Chengdu-Chongqing Economic Circle with 16 cities as research subjects.A comprehensive evaluation index system was constructed to measure the resilience of each city from 2003 to 2020.The spatial-temporal evolution characteristics were analyzed using Kernel density estimation,standard deviation ellipse,and spatial Markov chain analysis,and the spatial Tobit model was introduced to discover the influencing factors.The results indicate the following:①Urban resilience in the Chengdu-Chongqing Economic Circle displays an upward trend,with the center of gravity moving to the southwest,and the polarization phenomenon intensifying.②The urban resilience level in a region has certain spatial and geographical dependence,while the probability of urban resilience transfer differs in adjacent cities with different resilience levels.③Urban centrality,economic scale,openness level,and financial development promote urban resilience,whereas government scale significantly inhibits it.Finally,this paper proposes countermeasures and suggestions to improve the urban resilience of the Chengdu-Chongqing Economic Circle.

The Impact of Digital Finance on High-Quality Development of the Chengdu-Chongqing Economic Circle

This paper developed a comprehensive evaluation system that was able to quantify the levels of high-quality development across the cities within the Chengdu-Chongqing economic circle,and investigate the impact that digital finance had on the cities’high-quality development and the underlying mechanisms through which it achieved this.This comprehensive evaluation system was constructed using statistical data from these cities for the period 2014 to 2020 while also taking China’s high-quality development philosophy into account.The key findings revealed that:(a)Digital finance was able to significantly promote high-quality development in the Chengdu-Chongqing economic circle;(b)Digital finance had a significant positive effect in promoting innovative,coordinated,green,open,and shared development;(c)Digital finance was able to stimulate the high-quality development in the Chengdu-Chongqing economic circle by boosting entrepreneurial dynamism;(d)Digital finance had a significant impact on the high-quality development of the axis areas,while its impact was less discernible in non-axis areas.The insights from this research offer a deeper understanding of the factors that drive high-quality development,the role digital finance plays,and the mechanisms through which digital finance is able to propel high-quality development at the city cluster scale.

Transformation power or development pressure:economic growth targets and urban carbon productivity

Maintaining moderate economic growth targets(EGTs)is the key for local governments to effectively implement the“carbon peak and carbon neutrality”goals under the refreshed development pattern.Utilizing panel data of 276 prefecture-level cities in China's Mainland from 2010 to 2020,and employing methods such as intermediary and threshold models,this study empirically analyzes the internal mechanism of EGT’s impact on urban carbon productivity(UCP).Our findings demonstrate that:①The overall EGT during the analyzed period is not conducive to improving UCP.This conclusion remains valid after a series of robustness tests.This effect is more pronounced in the central region and resource-based cities than in the east-west region and non resource-based cities.②EGT not only directly suppresses UCP but also exerts indirect negative impacts on UCP from three aspects:delaying the digital economy(DE),constraining financial expansion(FE),and hindering green technology innovation(GTI).This negative indirect effect is similar to or even surpasses the direct effect,suggesting that the internal relationship between EGT and“dual-carbon”goals should be re-evaluated from a new compound perspective.③EGT not only has a simple linear impact on UCP but also significantly exhibits a dynamic evolution pattern in inverted“U”shape.That is,as EGT continuously upgrades,a nonlinear impact on UCP emerges in the form of“promoting first,suppressing later”.This indicates that surpassing the“degree”limit for EGT will be detrimental to the improvement of UCP.This study broadens the scope of carbon productivity analysis by introducing a new perspective centered on EGT.The insights gleaned from this research offer valuable guidance for local governments to effectively manage economic growth expectations and promote the synchronized achievement of dual-carbon objectives.

Disparities in the impact of economic well-being on self-esteem in adulthood:Race and ethnicity

BACKGROUND Most studies have defined economic well-being as socioeconomic status,with little attention given to whether other indicators influence self-esteem.Little is known about racial/ethnic disparities in the relationship between economic wellbeing and self-esteem during adulthood.AIM To explore the impact of economic well-being on self-esteem in adulthood and differences in the association across race/ethnicity.METHODS The current study used data from the National Longitudinal Survey of Youth 1979.The final sample consisted of 2267 African Americans,1425 Hispanics,and 3678 non-Hispanic Whites.Ordinary linear regression analyses and logistic regression analyses were conducted.RESULTS African Americans and Hispanics were more likely to be in poverty in comparison with non-Hispanic Whites.More African Americans were unemployed than Whites.Those who received fringe benefits,were more satisfied with jobs,and were employed were more likely to have higher levels of self-esteem.Poverty was negatively associated with self-esteem.Interaction effects were found between African Americans and job satisfaction predicting self-esteem.CONCLUSION The role of employers is important in cultivating employees’self-esteem.Satisfactory outcomes or feelings of happiness from the workplace may be more important to non-Hispanic Whites compared to African Americans and Hispanics.

Techno-Economic Optimization of Novel Stand-Alone Renewable Based Electric Vehicle Charging Station near Bahria Town Karachi,Sindh Pakistan

Electric vehicles (EVs) are the most interesting and innovative technology in the 21st century because of theirenormous advantages, both technically and economically. Their emissions rate compared to fuel-based vehicles isnegligible as they do not consume fuel and hence do not emit any harmful gases. However, their bulk production,adoption and lack of charging stations increase the stress of power stations due to modern-day lifestyles. If Electricvehicles demand increases drastically then conventional power stations will not bear their demand and if theygenerate electricity by conventional means it will be very costly and may further add greenhouse gases. Therefore,this research provides the techno-economic assessment of a stand-alone renewable-dependent electric vehiclecharging station, excluding any burden on electrical utility. The proposed study is carried out in Bahria Town,Karachi, a city in Pakistan. In this study, HOMER Pro software was utilized for techno-economic assessment. Ahybrid system comprising solar Photovoltaic/Wind Turbine/Fuel cells and battery storage is included in the model.Solar and wind resources were taken from NASA’s website, where charging stations will be integrated. The overallresults show promising in terms of total Net Present Cost and the Cost of Energy which are 2.72M $ and 0.237 $,respectively. The total system generation is 3,598 Megawatt hours per year, and the total energy consumption is 885Megawatt hours per year.