## 6 Synergism Between Algorithms and Smart City Optimization
### The Application Effect of Algorithm Collaboration in Real Estate Management in Smart City  
In the construction of smart cities, real estate management and urban optimization rely on the fusion and analysis of multi-source data [64]. Improving the accuracy and efficiency of data processing has become a key link, which is of great significance for exploring the deep value of data and realizing efficient urban management. To achieve this goal, we need to start with the following aspects. First, we optimize the data preprocessing process to ensure data quality, which includes accuracy, completeness, and consistency. Data quality is compromised by factors such as sensor errors due to environmental conditions. By addressing these issues through cleaning, denoising, and outlier detection, we provide a reliable foundation for subsequent analysis. Secondly, efficient data fusion technology, such as the data fusion method based on spatiotemporal association rules, can be adopted to effectively integrate data from different sources, formats, and scales to improve data availability. In addition, introducing advanced data analysis algorithms, such as deep-learning and machine-learning algorithms, to intelligently mine the fused data and discover potential laws and trends provides strong support for real estate management and urban optimization. At the same time, attention should be paid to the synergy between algorithms to achieve complementary advantages between data fusion and analysis algorithms. For example, combining spatial statistical analysis with geospatial data mining can improve the accuracy of the analysis of real estate spatial distribution characteristics, and deep-learning algorithms can further improve data processing efficiency when processing complex data relationships. In addition, by building an adaptive algorithm adjustment mechanism, the algorithm can automatically optimize parameters according to data characteristics, thereby improving the overall data processing performance. In order to further improve the accuracy and efficiency of data processing, the following points should be paid attention to: first, establish a complete data quality control system to ensure the accuracy of data throughout the entire processing process; second, strengthen interdisciplinary research, draw on technical achievements in related fields, and provide new ideas for smart city data fusion and analysis; third, pay attention to the real-time and dynamic adaptability of algorithms to cope with the ever-changing urban environment and real estate market. Improving the accuracy and efficiency of data processing is the core task of multi-source data fusion and analysis in smart city construction. Of course, in the real estate management of smart cities, the synergy of multi-source data fusion and analysis algorithms is of great significance for promoting the rational allocation of urban resources [65]. By integrating various sensor data, social media information, citizen feedback, and geographic information system data, combined with advanced data fusion technology and analysis algorithms, we can deeply explore the spatiotemporal characteristics, utilization status, and potential value of urban real estate. This fusion not only improves the availability and accuracy of the data but also provides comprehensive decision-making support for urban planners and helps to efficiently allocate urban resources. First, the fusion of multi-source data can fully reveal the spatial distribution characteristics and utilization efficiency of urban real estate, providing a scientific basis for urban planning. Through accurate analysis of the current status of real estate, we can identify idle resources, over-utilized areas, and development potential areas in the city, thereby guiding government departments to reasonably adjust the nature of land use and optimize spatial layout.